Elastic NV (ESTC) 2019 Q2 法說會逐字稿

Good afternoon and welcome to the Elastic second-quarter fiscal 2019 financial results conference call. (Operator Instructions). Please note this event is being recorded. I would now like to turn the conference over to Anthony Luscri, Vice President of Investor Relations. Please go ahead.

Thank you. Good afternoon and thank you for joining us on today's conference call to discuss Elastic's second-quarter fiscal 2019 financial results. On the call we have Shay Banon, Founder and Chief Executive Officer, and Janesh Moorjani, Chief Financial Officer. Following their prepared remarks we will take questions.

Our press release was issued after the close of market and is posted on our website where this call is being simultaneously webcast. Slides which accompany this webcast can be viewed in conjunction with live remarks and can also be downloaded at the conclusion of the webcast on the Elastic Investor Relations website at IR.Elastic.co.

On this call today, our discussion may include predictions, estimates or other information that might be considered forward-looking statements within the Safe Harbor provisions of the US federal securities laws. While these forward-looking statements represent our current judgment on what the future holds, they are subject to risks and uncertainties that could cause actual results to differ materially.

These risks and uncertainties include those set forth in the press release that we issued earlier today, as well as those more fully described in our filings with the Securities and Exchange Commission, including our prospectus dated October 4, 2018 as filed with the SEC. You are cautioned not to place undue reliance on these forward-looking statements which reflect our opinions only as of the date of this presentation.

Please keep in mind that we are not obligating ourselves to revise or publicly release results of any revision to these forward-looking statements in light of new information or future events unless required by law.

In addition, during today's call we will discuss certain non-GAAP financial measures. These non-GAAP financial measures, which are used as measures of Elastic's performance, should be considered in addition to, not as a substitute for or in isolation from GAAP measures.

Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation, amortization of acquired intangible assets, acquisition-related expenses and non-GAAP tax rate adjustments. You can find additional disclosures regarding those non-GAAP measures, including reconciliations with comparable GAAP measures, in the press release and on our Investor Relations website in the slides accompanying this webcast.

The webcast replay of this call and slides will be available for two months on our Company website under the Investor Relations link. With that I will turn it over to Shay.

Thank you, Anthony. It's good to be here today and have everyone listening in on our first earnings call as a public company. I'd like to start by taking a moment to thank our wonderful community of users, customers, developers, partners, investors and our employees and their families for contributing to our success.

Q2 was a special quarter on many fronts, but ringing the bell on the New York Stock Exchange on October 5 was a very special moment for us. While it was a truly remarkable day, it was only one day in a long-term journey and there is much more to tell with our story.

With that in mind, I'm pleased to share some high level results from our very strong second quarter. In Q2 revenue grew 72% year-over-year to $63.6 million. We had more than 6,300 subscription customers at the end of the quarter, including over 340 with annual contract value of more than $100,000. And our net expansion rate was over 130%, which we have maintained for eight quarters in a row now.

Before Janesh gets into the details of financial performance, I would like to provide an overview of our business for those who are new or less familiar with Elastic. I will also highlight some recent product announcements and customer wins.

Elastic is a search company; we believe search is foundational for a wide variety of experiences and use cases. You may not realize it, but you probably use Elastic every day. When you catch a ride on Uber, we are the engine that matches a driver with you. When you look for groceries on Instacart, Elastic provides you with relevant results and recommendations. When someone swipes left or right on Tinder, Elastic is what powers finding a match they might like and who might like them back.

Now, all of these experiences I just described need to be monitored, checked and observed. Elastic powers that too. So customers like Tinder and Barclays take their infrastructure logs or remote server metrics and put them into Elastic to understand what is working and what is not, both on the technology side and on the business side.

And if you think about it, it doesn't take much to go from analyzing machine data to analyzing security events. So a customer like Indiana University can build their cyber security operations on top of Elastic in order to protect thousands of devices and critical data. Everything I just talked about in search.

But what is it about our search technology that makes us different? Three things: speed, scale, relevance. If something isn't fast that's a problem. Users won't wait minutes for results to appear on sites like Wikipedia. Why should they wait for any other use case? If something takes more than a second we cringe inside. It's all about having a discussion with your data, not running a query and stepping away to make coffee only to come back and forget what questions you asked in the first place.

At the same time, you need to have these fast experiences at scale. So going from one laptop to thousands of machines, it should all still operate the same. And it is not acceptable to be fast and scalable and then return lousy results. So relevance is critical here. These three elements: speed, scale, relevance -- they are at the core of the Elastic Stack.

Now at the heart of the stack is Elasticsearch. It is what stores, searches and analyzes data, structured or unstructured, and it is what everything gets built around. Beats and Logstash are ways to ingest data into Elasticsearch from many sources and Kibana is how you visualize data in Elasticsearch.

We also build solutions that are vertically integrated into our Stack. They include App Search, Site Search and Enterprise Search, Logging, Metrics and APM, business analytics and security analytics. You can think of solutions as ways we've made it easier for users to get started with our software to address a particular use case. For example, today with our Logging solution you can start analyzing log files or add search to your website with our Site Search service in a matter of minutes.

We also give users the flexibility to deploy our software the way they want. For our SaaS managed offerings, they download the software and then manage it themselves on prem in a public cloud or a private cloud or even in hybrid environments. We also provide a hosted service, Elastic Cloud, which is our family of SaaS offerings and it includes our Elasticsesarch Service, Elastic Site Search Service and Elastic App Search service.

We've also found that as customers grow their self managed Elastic deployment and scale to many projects and many clusters, they want to enjoy a SaaS-like experience to centrally provision, manage and monitor our products. Elastic Cloud Enterprise, or ECE, let's them do that. It is a paid proprietary product that customers download and run in the environment of their choice.

As we consider our market opportunity we believe that it expands for current use cases and also as our technology deploys towards new use cases. For example, when we founded Elastic many of our users took our product and applied them to solve use cases like App Search and Enterprise Search.

And as we stated previously, this space had a total addressable market of $3 billion back in 2012. As our users deployed our products to power new use cases and we expanded our offerings, our TAM has grown to $45 billion in 2018.

I will also take a minute to talk about our business model. It starts with our distribution model. We have an open source approach to distributing our software, which allows rapid adoption and innovation for our millions of users with little investment.

And what this means is that users have an opportunity to experience the value of our products long before they ever speak to a salesperson. And by the time they do it's a warm customer value driven conversation. We have a sense of who they are, what their projects look like and what they are hoping to accomplish with our products.

Our business model is based on a combination of open source and proprietary software that we make available through paid subscription which also includes support. Some of our proprietary features, like Monitoring and Canvas, are free. And some proprietary features like machine learning and security are paid.

It's also important to note that we do not build a separate enterprise grade version of an original open-source project like some companies do. Instead, we develop and test one codebase that we control. This allows us to guide and direct our products to meet the needs of our users more efficiently. So it's this combination of free and paid offerings, alongside our open source roots and distribution model, that has really allowed us to build a thoughtful, user driven, commercial business model on top of open source.

As I reflect on customers and product activities over the past several months, I'll start by saying that we traveled a lot, specifically for our Elastic[ON] Tour events, to engage with our community of users, customers and partners. These events are designed to deliver training and helpful content to our users that cover recent product development.

We went to 11 cities, including Melbourne, Sydney, Boston, Chicago, Toronto, Minneapolis, Denver, Washington DC, Stockholm, Frankfurt and Santa Clara. We are in our fourth year of hosting these event and we are humbled by their popularity.

A few weeks back I attended the Washington DC tour event. It attracted over 800 people and I was amazed to see so many users building their future on top of us. As you might imagine, security is an important topic in the public sector.

For many years we have invested in creating really powerful security features ranging from basic authentication and encryption to granular access control at the document, field and attribute level.

And at this DC event I noticed there was a lot of discussion around new security features we released in this quarter. This included support for running Elastic in FIPS 140-2 mode, which is critical to the [fab] space, and (inaudible) authentication, which has broader applicability to not only government audience but also to larger enterprises across the world.

Take a company like Liberty Global, one of the largest telecom companies in the world. They became our customers thanks to our advanced security features that I just mentioned, as well as our world-class support and additional commercial features. They are using us to analyze their log data, monitor systems and investigate intrusion events. The expanded their usage with us in the second quarter because of the further rollout and innovation of their next generation platform called Horizon 4.

It was also amazing to see the positive reaction at our tour events to the prerelease of our cross-cluster replication paid for feature, which was in our 6.5 release a few weeks ago. This feature is important for fast searches and data locality, it is also important for high availability and disaster recovery. So we are excited to offer this robust and highly requested feature that will support search and replication across multiple public and private environments including hybrid clouds.

Another highly requested feature we released is Kibana Spaces. When users adopt Elastic and start ingesting data, one of the first things they do is create a handful of visualization and dashboards. That handful often grows to be hundreds or even thousands very quickly.

And we saw that users needed a better way to organize their visualizations into defined workspaces, one for the marketing team, another for dev ops, another for finance and so on. Kibana Spaces makes this possible by allowing users to segment and secure Kibana for different audiences and use cases.

Speaking of different audiences, I am particularly excited about the prerelease of another Kibana feature that we call Canvas. We are inspired by the fact that our users are proud to display their data. And we took this to heart and spent the last year working on Canvas to give users a personal way to display living dashboards that are not just pleasant to use but also pleasant to look at.

It has been fascinating to see the adoption of Kibana in the places you would expect like a network or security operations center, but over time we've seen it in less expected places, like office entrances and executive board rooms.

To give you an example, Brazil's Ministry of Health renewed their business with us in Q2 through one of our partners. They have Kibana dashboards on permanent display in the health minister office. They show real-time health spending and service quality information that is aggregated from 400 databases and systems. This is awesome.

I am excited about how easy it will be for them to deploy Kibana Spaces and Canvas to further share and visualize information across their organization. Hopefully when I visit Brazil next year for our tour I will see them both in action.

In the Logging and Metric use cases we are continuing to execute well and are seeing strong momentum. Oracle's cloud native engineering team selected Elastic software to help accelerate development and operations of common cloud services running in Oracle cloud infrastructure to support multiple SaaS applications.

Elastic's products allow for rapid collection, presentation and analysis of logs and key performance indicators. We've also doubled down on making it even easier for people to implement Elastic for the Logging and Metrics use cases. Recently we previewed two new user interfaces that provide curated experience for logging and monitoring various aspects of infrastructure. So things like servers, Kubernetes pods, Docker containers and services.

We've also [previewed] an easier way for users to ship data from more data sources like serverless applications and cloud services and efficiently summarize data to save on space with rollup support in Kibana.

So as I talk about these features, I think about how they could streamline Logging and Metrics for customers like the car2go Group, one of the largest carsharing companies in the world and a subsidiary of Daimler AG. They use Elastic to do things like monitor car connectivity and detect fraud by analyzing logs and metrics from Kubernetes and Docker, payment services as well as physical and virtual machines. In the second quarter we renewed and expanded with them and I look forward to them getting started with our new Logging and Metrics UIs.

Related to this is APM, which is another area where we are continuing to invest by enabling our Logging users to simply add APM data into their workflows. And I'm happy to share we recently integrated machine learning into APM and released support for additional programming languages like Java and Go. We also previewed distributed tracing feature that lets users observe how application requests flows through services.

We also had exciting development in our SaaS business this past quarter. We enabled a major feature on our Elasticsesarch service that gives users more freedom and control over how they deploy our products. We've made it easy for users to deploy custom topologies like hot-warm architectures, which is especially useful for Logging use cases.

What this means is users can separate their deployment into hot and warm data nodes so they can query recent data quickly while retaining older data for longer periods of time without breaking the bank. For example, the wireless sound system company Sonos is a new Logging customer of ours that is analyzing sound device diagnostics and player telemetry. They chose our hosted Elasticsearch service offering because of these features and upcoming developments that only we can provide.

It is worth pausing to remind everyone that we are the only offering that provides features like Canvas, [rollups], logs and infrastructure UI and many others that I mentioned earlier. No one else does.

This is also true for the custom topologies feature I just talked about. We are the only hosted Elasticsearch offering that provides this flexibility. I am particularly excited about this feature because it allows our users to more efficiently run our products and manage costs. It also makes it easier for users to adopt our service or move self-managed workloads to a SaaS environment if they want. We also change and enhance our SaaS pricing model in order to reflect this flexibility.

Now all of these SaaS features I've just mentioned, we've also made them available in our 2.0 release of ECE. The new release makes the complexity of managing multiple Elastic Stack environments simpler with many new features such as host tagging, customizable deployment templates including hot-warm architecture, automated [in-depth] curation and more.

For instance, we expanded our relationship with one of the largest US broadband providers. A few years ago they started out with a few nodes of open source and then grew to become a [gold] subscription customer. As of Q2 they are an enterprise subscription customer using ECE 2.0.

The company uses ECE for logging use case, ingesting 15 TB of machine generated data per day, over 200,000 events per second providing real-time visibility into everything occurring in their content delivery network. We believe this is a great validation of the value of our ECE product as well as our business model.

As you can tell, we saw strong momentum with our products and customers in Q2. Beyond the many customer stories I just highlighted, we saw a number of other notable wins. We also continue to invest heavily in all parts of the business, growing our engineering team, expanding our marketing reach and our sales coverage and investing internally for scale.

I will close by saying that we are very pleased with our Q2 results. With the continued strong demand across our business we are uniquely positioned to capture the tremendous opportunity in front of us and we are pursuing it aggressively. And with that I will hand it off to Janesh to talk about our financial results in detail. Janesh?

Thanks, Shay, and thanks again to everyone for joining us. To our new public shareholders, we enjoyed meeting many of you on the road show and look forward to building a long-term relationship with you.

Because this is our first earnings call and some may be new to the Elastic story, let me first go over some important aspects of our business model. Approximately 90% of our revenue typically comes from subscriptions which represent recurring revenue. Our subscriptions for self-managed deployments generally range from one to three years for which we typically invoice customers annually in advance.

Our SaaS customers purchase subscriptions either on a month-to-month basis or on a committed contract of at least one year in duration. Subscription fees typically vary based on subscription levels and the underlying memory and storage.

The remainder of our revenue comes from professional services which consist of consulting and training. The primary objective of our professional services team is to make our customers successful, which in turn drives higher subscription revenue as these customers expand their usage of the Elastic Stack and our solutions.

Our direct sales team is organized by geography and by customer segments and we have a growing partner ecosystem. As Shay mentioned, our sales and distribution approach starts with a massive top of funnel that is fueled by the strength of the open source distribution model.

Because users deploy our software long before they engage with a sales rep, sales engagements often start with warm leads and in many instances there is existing executive mind share. All this leads to efficient sales cycles.

There are a number of levers that drive our growth. I just touched on how we expand our customer base by acquiring new customers with an efficient model. Our customers also often significantly expand their usage of our products over time. Expansion includes increasing the number of users using our products, increasing their utilization of our products for a particular use case and applying our products to new use cases.

Our net expansion rate, or NER, is one measure of this. NER indicates the average increase in the spend of existing annual subscription customers net of churn compared to one year ago. Our net expansion rate has been more than 130% in every quarter for the past eight quarters including Q2.

With that let me move to our second-quarter results. I would like to thank our employees for their hard work as we had both a strong second quarter and successfully executed our IPO. As Shay mentioned, total revenue for the second quarter was $63.6 million, growing 72% year-over-year.

Subscription revenue totaled $58.4 million, an increase of 68% year-over-year, and comprised 92% of total revenue. Within subscriptions, revenue from our SaaS products was also strong at $10 million, growing 79% year-over-year. We launched a significant update to our SaaS services, offering customers much more flexibility, and we revised our pricing model in conjunction with that. We're excited about this change and the SaaS opportunity ahead of us.

Professional services revenue was $5.1 million, an increase of 128% over the same period last year. Professional services revenue is typically recognized at the point in time the services are delivered and therefore can fluctuate quarter to quarter. We expect professional services will remain a small proportion of our overall revenue as our business grows.

In terms of geographic breakdown, given our roots in open source and our globally distributed model, [40]% of our revenue came from outside the US with the majority of this coming from EMEA. We are very proud to have achieved such geographic diversification so early in our life as a company. We believe we have a rich market opportunity outside the US and remain dedicated to investing appropriately to capture that opportunity.

Moving on to calculated billings, we define calculated billings for any quarter as total revenue recognized in the quarter plus the sequential increase in deferred revenue as presented on our statement of cash flows less the sequential increase in unbilled accounts receivable. Calculated billings in Q2 was $88.5 million, an increase of 73% year-over-year.

Calculated billings can fluctuate from quarter to quarter based on the timing of renewals and billings duration for larger customers. We also tend to see our strongest billings in the second and fourth quarters as a result of the buying patterns of our growing customer base.

Given these factors, an additional way to look at calculated billings growth is on a trailing 12-month basis which provides a longer-term view of the business. Trailing 12 month calculated billings growth ending Q2 was 77%.

We were very pleased with the calculated billings growth this quarter and the underlying demand that is driving our business. The strong growth in Q2 was driven by a broad array of growth vectors including new customer additions, new use cases at existing customers and larger deployments.

As of the end of Q2, we had over 6,300 paying subscription customers compared to over 5,500 such customers at the end of Q1. We continue to see strong momentum with new customer additions. We also remain focused on growing the number of our larger customer accounts and ended the quarter with more than 340 customers with an annual contract value above $100,000 compared to more than 300 such customers at the end of Q1.

Our existing customers continue to expand their relationships with us, reflecting increasing spend for existing use cases and adoption of new use cases. As I mentioned earlier, our net expansion rate remained over 130% for the eighth consecutive quarter. When viewed collectively these customer metrics provide insight to our execution against the enormous market opportunity ahead of us.

Now turning to profitability and other results which are all non-GAAP. Gross profit in the second quarter was $46.6 million representing gross margin of 73%. Total subscriptions gross margin was 80% compared with 82% in Q1. As planned, we continued to make investments in the SaaS business in Q2 and are tracking well relative to our expectations.

In addition, I earlier referenced the more flexible pricing model together with the new SaaS features launched in August. In conjunction with scaling the adoption of our SaaS offerings, we also anticipate driving reductions in underlying unit hosting costs. In the near-term SaaS will remain a modest headwind to gross margin overall. Over time as the business scales and as we capture the significant market opportunity ahead of us we expect to drive natural gross margin improvement.

Our professional services gross margin was negative 4.9% as we added further capacity in advance of revenue and as existing hires ramp to productivity. As a reminder, since the professional services business is small, even relatively insignificant amounts can swing the gross margin in either direction. So we expect that the gross margin in professional services will fluctuate significantly from quarter to quarter.

Turning now to operating expenses, we remain focused on investing to drive top-line growth. Sales and marketing expenses for Q2 was $31.8 million, up 97% year-over-year, representing 50% of total revenue. While we expect to realize leverage in sales and marketing as we scale the business, our primary near-term focus remains adding sales capacity and expanding market coverage as we drive growth.

I'll also point out here that we replaced our annual Elasticon user conference, which in the past happened in Q4, with a series of local events spread over the course of the entire year. Shay mentioned our two locations from Q2 earlier.

R&D expense in Q2 was $20.5 million, up 88% year-over-year, representing 32% of total revenue. R&D remains a major investment area as we expand our innovation advantages. We don't see open source as a mechanism to outsource R&D to the community. In fact, as the sole commuters of code, we believe it is important for us to invest heavily in R&D to both widen and deepen the portfolio.

G&A expense was $9.2 million, up [80]% year-over-year, representing 14% of total revenue. This includes costs associated with our global expansion and continuing to build the infrastructure to scale for the future. Our operating loss in the quarter was $14.8 million with an operating margin of negative 23%. Overall we continue to invest at a consistent pace in the business compared to recent quarters as we continue to drive strong growth.

Net loss per share in Q2 was $0.38 using 44 million basic and diluted shares outstanding. This compares to a net loss per share in Q2 of last year of $0.17.

Free cash flow was negative $1.4 million in Q2 compared to a positive $3.6 million in the same period a year ago reflecting the investments we are making in the business. Although we are slightly positive year to date on free cash flow, there are seasonal effects. Free cash flow is seasonally stronger in the first half, particularly in Q1, and weaker in the second half.

There can also be some lumpiness to inflows and outflows. So we look at it mainly on an annual basis and expect the full year to remain negative. While we don't formally guide to free cash flow, we expect to continue to gradually improve free cash flow margin on an annual basis, but it may not be in a linear trajectory given period-to-period fluctuations.

Turning to the balance sheet, we ended the second quarter with $318.6 million in cash and cash equivalents. We raised approximately $264 million in our initial public offering in October net of all expenses, including some that remain payable at the end of the quarter. Lastly, we ended the quarter with 1,129 employees, adding 135 people in the quarter across all functions.

Moving on to guidance, before I provide the outlook for Q3 and the full year, let me share with you our investment philosophy. Over the near- to mid-term, given the significant market opportunity, we expect to continue to invest in our go-to-market operations, people and infrastructure to drive future top-line growth.

In addition, innovation remains a top priority for us and we will continue to invest in R&D, as well as pursue inorganic opportunities to pull our future into the present such as the Insight.IO acquisition announcement that we made earlier this year. Long-term profitability is an important objective for us and we see multiple paths to achieving long-term profitability goals depending on how fast we can continue to grow the top line.

Turning specifically to the third quarter and the full-year fiscal 2019. For the third quarter of fiscal 2019, we expect revenue in the range of $64 million to $66 million, representing a growth rate of 56% year-over-year at the midpoint. We expect non-GAAP operating margin in the range of negative 30% to negative 28% and non-GAAP net loss per share in the range of $0.32 to $0.30, using approximately 71 million ordinary shares outstanding.

For the full year of fiscal 2019 we expect revenue in the range of $254 million to $258 million, representing a growth rate of 60% year-over-year at the midpoint. We expect non-GAAP operating margin in the range of negative 26% to negative 25% and non-GAAP net loss per share in the range of $1.35 to $1.30, using approximately 56 million ordinary shares outstanding.

In closing, Q2 was an exceptional quarter. We delivered top-line growth of 72%. I am very excited about the strong results in our momentum and we continue to invest in the business given the significant market opportunity ahead of us. I look forward to sharing our progress with you throughout the rest of the year. With that let's open it up for questions. Operator?

(Operator Instructions). Heather Bellini, Goldman Sachs.

Congratulations on your first quarter being public. I was wondering if you can share a little bit -- I was looking at the customers with ACV over $100,000, and there was a net increase this quarter of 40,000 which had great growth of 70% year-over-year in total.

I was wondering if you can share with us how you see the split between existing customers ramping their deployments and, as such, getting to that greater than $100,000 number as time goes by versus the number of customers that are attaining that status in their first purchase. Are you seeing the balance between what you've normally been seeing there start to change? Thank you.

Thank you very much for the compliment. We are very excited about our first-quarter and being a public company and we are very excited about the results and thank you for covering, obviously, as well.

So we are -- personally and as a company we're very happy with the balance between both new customers that ends up spending more than $100,000 with us and existing customers. This is reflected by the fact that, first of all, we are very happy with our NER number, which means that customers that start to spend with us grow in their spend with us year-over-year.

We like to also start small. This is part of our distribution model. This is part of a small project starting using our software, zero to no touch from us and then immediately starting to see value through the products themselves and then eventually engaging commercially with us and then growing within the organization.

But also at the same time we do see opportunities that ends up being reflected through large deployments from the get-go. That tends to be logging or security type deployments. I think Indiana University is a great example of a win versus Splunk in this case in the context of the security space. And we also see these new customers coming in directly above $100,000.

Okay great. And then just a quick follow-up if I will then. Is it fair to say then that you are starting to see the average or the initial purchase of Elastic get bigger, like the initial bite at the apple is becoming larger from customers? Is that fair based on your comments you just made?

In terms of the ASPs or deal sizes, broadly I would say they are roughly consistent with where they have been. It's still early innings for us. As I look at the numbers here in Q2, it was perhaps slightly higher than it's been in the past, but I wouldn't necessarily call it a significant uptick or a trend at this point time. But we are still pretty bullish about the future.

Mark Murphy, JPMorgan.

I will add my congrats on the robust results. So Shay, I wanted to ask you at a very high level, how important do you think machine learning technologies are going to be for the future of Elastic in areas like anomaly detection and root cause analysis and also other areas?

And also, just given the strength of the relationship that you have had with Google and Google Cloud, how do you think you can best fit in and leverage some of the frameworks like [sensor flow]?

Let me address the questions specifically. So first of all, we are great believers in machine learning, specifically in the context machine learning is very broad. In the context, as you mentioned, of anomaly detection, this is reflected by the fact that we acquired a company called Prelert almost three years ago, deeply believing in the fact that once data is in Elasticsearch magic can happen. And part of it is the ability to automatically detect anomalies and then being able to immediately go and send it to the user.

I will mention that part of the beauty of our stack is the fact it is fast, it is very fast. So first of all, users can go and suddenly refresh dashboards that they never thought would get refreshed within milliseconds and then being able to see the results of it.

And obviously that's immediately reflected by the ability to apply machine learning algorithms on top of the data. The fact that we can render dashboards very fast also means that we can run machine learning algorithms on top of it very fast. So that is one aspect.

The other one, to address your second question, we've built a foundation where you can store your data and execute search queries and search algorithms on top of that data, as I mentioned, in an extremely fast manner. Our stack has always been extremely open.

So if you go and, for example, see what the community has built on top of our stack, you would see integrations with TensorFlow, integration with [R], integration with [Pandas] and other very popular machine learning libraries. And obviously we are helping help the community drive this level of innovation. So that is one tier, so we definitely see that level of development and it's happening every day.

But also we are developing our own set of machine learning algorithms and built-in features that are integrated directly into the stack. If I had to qualify between the two I would say that our focus is more for more self-sufficient machine learning algorithms that don't require someone to be a data scientist to run them; that's reflected by our anomaly detection feature. At the same time obviously someone that knows how to run Tensorflow or Pandas or R, they are more on the proficiency level of a data scientist.

To finish it, to touch on your point about Google, first of all we are super excited about the relationship we have with Google and the fact that we are the official search or Elasticsearch hosting provider on top of Google Cloud together with Google or the Google Cloud platform.

And we are very happy with the fact that when data is stored in Elasticsearch you can go and run almost any type of Google machine learning algorithm out there on top of that data in Elasticsearch. That's very easy and very simple integration. So all of the innovation that Google does in machine learning immediately applies to the benefit if someone ends up putting data in Elasticsearch itself.

Janesh, as a quick follow-up, as the product stack is going to be evolving here over many, many years, where do you see the longer-term mix of Logging in terms of both the use cases and I guess the Logging-related revenue? Where do you think that would settle out? I think that it has currently been running around a third in terms of the use cases.

So just in terms of a little bit context to that, when we think about use cases and different projects, very often a project can actually span multiple use cases. A great example of that is a customer decides to put a search box on a website and you can call that a site search use case. But they are also then reading the log files and analyzing those using the Elastic Stack.

And so, that's a case where it touches two different use cases, which is why within our own CRM systems as we try and track that information, it's a multi-picklist and any project can have multiple use cases assigned to it. And as we look at that data, Logging represents a little bit over a third of the self reported use cases from that standpoint.

Over time obviously we are super excited about the opportunity in Logging and security more broadly. That represents significant opportunity for us. But one of the things that has really made us successful is following the community and evolving the stack and the features in the stack based on what the communities and users needs are.

So, I can't look ahead and tell you it that will be a significantly larger or smaller portion. We will take that as it comes. Right now we're just pleased with the execution we are seeing against Splunk in the logging space.

Raimo Lenschow, Barclays.

Congrats from me as well. Shay, since it's the first quarter post the IPO, can I ask a more basic question? I was wondering -- like I used to cover the first generation of search guys that were proprietary like the Autonomys and the FAST Search. And I know you've been loosely engaged as well with the other open source projects around UCs. What makes Elastic so special? Why did the other guys not succeed where you clearly are seeing a lot of success? And then I have a follow-up for you, Janesh.

Maybe I can touch on it a bit. First of all, ever since we created Elasticsearch and then when we formed the Company, our goal was to try to build a product suite that allows for very easily add many different types of data sources on top of Elastic, whether it is through the ease of use of the API driven development, whether it is through the ease of use of creating visualization for many different use cases.

Whenever we develop a feature we think about it from a [PO] or search perspective, and then we are always curious about the fact how will that end up applying to many different use cases and new use cases down the road.

I would say previous companies, even though they had sometimes similar vision, by the way, when they started, they ended up constraining themselves towards the enterprise search use case. And for that reason when you constrain yourself to a specific use case you end up communicating it to your user base.

I like to say that when I created Elasticsearch, I never thought that someone will end up taking a log message or log file and end up putting them in Elasticsearch. I was 100% sure that [search priced] too many use cases, I just didn't know which ones.

But then someone decided to put a log message in Elasticsearch and they decided to put the log message in Elasticsearch but not in any type of the enterprise search products out there. They decided to put the log message in Elasticsearch and not in any of the no SQL solutions out there. They decided to take a log message and put it in Elasticsearch and not into Hadoop vendors out there, especially in the early days.

And that speaks to the fact that we are building products that allow people to innovate and imagine what can happen when they put different types of data into Elastic and then see the results of it.

And Janesh, can you just give us an idea about your -- the framework you are thinking around cash, because you've been much, much better than a lot of the other growth companies around cash generation and how you run the Company. Is that kind of like the framework around cash breakeven? Is that kind of the right way to think about it? Or what other scenarios do you kind of move away from that one?

In terms of cash investments, we actually think that the appropriate thing for us to do at this point time is to invest in the business. And so, if I think back to fiscal 2018, our free cash flow margin was negative 15%. We've been skating close to positive or breakeven here in the first half, but that is really the effects of seasonality. There are seasonal effects here in the cash flow. The back half tends to be seasonally weaker and that's mainly because of strong collections that we typically have in Q1.

So we look at it really on an annual basis ourselves. And we expect that from a full-year perspective the free cash flow margin will be negative. We don't formally guide to it, as I mentioned in my prepared remarks, but we do expect to see some improvement in free cash flow margin over the course of this year and on an annual basis, but it won't be a linear trajectory. Right now we are still focused on investing to drive growth.

Perfect, well done, congratulations.

Matt Hedberg, RBC Capital Markets.

I will offer my congrats as well. Shay, on the call you gave a few examples, but I'm wondering if you can give a few more details on the adoption of your Elastic Cloud enterprise offering. What customers are you seeing are the primary adopters there? And is there a particular preference for where these customers are deploying ECE?

Hi, Matt. Thanks for covering us. Our ECE product, which is part of our enterprise subscription, is geared towards the more higher tiered type spend of our customer base. It is definitely priced like that. And our go-to-market with it is I would say twofold.

The first one is, as I mentioned in our adoption model, we start to see people or customers or companies adopting us in one project and then another and then another. And you suddenly see 20, 30, 50 projects. Very different use cases, by the way. Some of them we exclusively define, some of them can be fraud or others that always keeps on surprising us, to be completely honest.

In that case once a company needs to manage 20, 30, 40, 50 clusters or 50 deployments of Elastic, we can give them the product that will basically make it into a seamless experience -- a SaaS like experience, if you will -- within their own deployments and within their own infrastructure. So that's one aspect of ECE.

The other one is we see customers wanting to go and deploy Logging as a Service for example, so I call it Use Case as a Service for the rest of the organization. They start with one project and see that it is very successful. In the Logging projects they suddenly look around and ask who is using Elastic for Logging, and suddenly there's five or six more teams that raise their hands and say they use us for logging as well.

And then they used ECE as a way to provide Logging as a Service again in a SaaS like experience. It is exactly the same as you go to our SaaS service, and provide it to the rest of the org. And that is critical. That's like another level of multi-tenancy that people don't necessarily expect to have.

And we worked really hard to make sure that our user base or our customer base wound up having this SaaS like experience within the org if they want to when it comes to Use Case as a Service.

So, those are two typical use cases or to typical patterns that I see of the adoption of ECE that I am super excited about. And obviously that works towards it being more of a high end product and something that will end up selling when the increased usage of Elastic ends up going above a specific threshold.

Super helpful. And then, Janesh, your international exposure at 40% is impressive for a company of your size. Can you talk about the rate of pace of investments overseas? I know it's primarily in Europe, but just sort of wondering how you think about deploying dollars internationally relative to the US opportunity.

So, in terms of the investment profile, I'd say we are investing really in all geographies and segments at this point in time. We aren't necessarily focused on limiting it to certain parts. We have made three significant investments across the world in Asia-Pacific and Europe and clearly right here in the US there is enormous opportunity.

So, as I think about where we are adding not just sales capacity but all the other elements of the go-to-market operations that help make a sales rep successful, it's really across the board in every geography that you can think of.

Thanks guys. Well done.

John DiFucci, Jefferies.

Janesh, you said you are in early innings here; and, Shay, thanks for going through all the technology in all the use cases. By the way, Shay, I think that guy or that woman who log messages in Elasticsearch, you owe them at least a beer if not a few shares because that was great. But it made me think of something else.

I think Elastic and I think of all the various use cases it's being used for. And I'm just curious, are there any new use cases starting to emerge like Logging that you didn't anticipate? And even things that perhaps we didn't have solutions for and now people are like, you know what, we can actually solve this problem we never could before.

Because when I look at the opportunity for Elastic, and I can look at log analysis and I can look at APM and I can look at all those defined markets. But something inside tells me that there's a lot of other things that I haven't defined yet. And you are going to see that before anybody else does. And I'm wondering if you are seeing any of that yet.

Sure. Thanks, John. And by the way, we did I hope better than just buying that person a beer; we actually hired them. So we're very happy with them being with us in the Company and obviously I say thank you every day that I see them. But yes, so maybe I can address it.

The first bit I would say is that actually we treat APM and security, and to a degree business analytics as well, as the early innings of these use cases. Specifically, for example, if you look at security and APM, it feels to me and the way that I judge it is the way that we saw Logging five years ago.

So it's only getting started. We are in the process of making sure that the experience is smooth for the user. We are doubling down on that use case creating curated UIs, curated injection of data sources, everything that the user expects us to have as a Logging solution. And I would argue that we have it today and even this last quarter you've heard about this dedicated infrastructure UI that we built and logs UI and the integration with new systems like Kubernetes and Docker and others.

So when it comes to security and APM we are just in the beginning. Actually the way that we positioned APM is not as a replacement to other APM vendors; we just think it's a net add to any Logging and Metrics solution out there that we have customers using us today.

Also I would like to call out Canvas as another -- something that is early innings as well. Canvas is a way to take data that exists in Elasticsearch and expose it to a whole new audience that we didn't necessarily see. And I will admit, this is something that we saw happening and then we ended up developing it as a result of it.

So when I would go and visit customers, whether it's walking through the customers' halls and see Kibana dashboards on screens in their office entrances, or talking to CSOs and CIOs and seeing those screens on their main screens in their office. And I would cringe a bit inside because that is a dashboard that I would want to use as an operator, not necessarily a dashboard I would want to use and put as an entrance to my office.

So we've developed Canvas to try to expand the data that exists in Elastic to other audiences. So those are, to be honest, because we are an open company and an open source company, what we are doing and how we are moving forward and the investments that we do is out there.

And we are very open with you and with the community around what we develop, but some of these projects are in the early stages of them. Canvas has been in development for a year and has been out there for almost nine months now. So we are super excited about the investments that we do in these three segments, for example, and see where they take us.

Great and we appreciate the openness. Janesh, I'm looking for a numbers question, but I appreciate that the numbers sort of speak for themselves this quarter. And really nice job, guys. Congrats.

Kash Rangan, Bank of America Merrill Lynch.

Congratulations on your first quarter as a public company. Shay and Janesh, we did a survey of enterprise search and we were stunned to find out that the majority, 90%-plus of respondents were actually using legacy technologies for search. I'm curious how you see (multiple speakers) office you put Elastic in that its current generation technology vis-à-vis the old landscape of owned legacy search technology.

Secondly, as you get into the next 12 months, how does your sales capacity growth plan look like? Thank you very much and congrats.

Maybe I can address the first one. It was a bit spotty, but I think I got the question. So if I may repeat the question for a second, the way I understood it is: there are a lot of search products out there today already that don't necessarily use Elastic, but people are super excited about using Elastic in order to solve them. So how do we see the opportunity in that context?

And I would say that I am also super excited about it. That is the beauty of what we've built. The use cases are out there and some of them are actually we can go and put a whole breath of fresh air into them.

So specifically, for example, we acquired a company called Swiftype and, as a result of it, we immediately got the ability to add a search box to your website with Swiftype site search. Within minutes we go and call the websites and create this customized UI and what have you.

But also Swiftype developed this enterprise search product that I am super excited about. It's better today -- it is enclosed better today. We did -- we directed the investment in Swiftype when we acquired the company towards Site Search and what we call App Search. But we are super excited to get back to Enterprise Search and invest in creating this, as we call, use case or solution based product that makes replacing or investing in just new projects in the Enterprise Search market.

And Kash, just to touch on the bit about the sales capacity, to give you a sense, we added 135 people in Q2. If you sort of think about general industry trends and ratios of how many people tend to be in sales and marketing and industry standard ratios around sales reps and so forth, our numbers will look and feel similar to that. So you can get a pretty good sense of how we are adding sales capacity.

Looking ahead for the next few quarters I would say we will continue to invest as quickly as we can. I think it also just comes down to how quickly we can actually hire people and just the physics of the laws of execution, if you will. There is that piece that plays into it.

And then, as you hire people in certain territories you want to give territories time to mature, time to settle, help people ramp to productivity pretty quickly before you start to -- if you inject too much capacity too quickly it can actually have an unintended consequence. So we are just thoughtful about that piece as well. But fundamentally we are investing as quickly as we can to spur growth for the future.

Tyler Radke, Citi.

I was just curious if we could just talk a little bit about philosophically how you are approaching reinvesting back into the business. Obviously the quarter and the top-line guidance was very strong, but it looked like you are taking most of that upside and deploying it back into the business where you're seeing good return. So, do you feel like you are almost under hiring at this point? And what are the primary areas where you feel like you need to invest the highest?

So in terms of the investment profile, as you mentioned yourself, I think for us it's all about investing to capture the opportunity that is ahead of us. That is where we are focused at this point in time. We are actually quite pleased that we are able to take at least some of the upside, if you will, and see that translate into a little bit of upside on the bottom line as well.

But looking ahead, you will see that we reflected in our guidance that we will continue to invest as we drive upside in the business. That's a focus area for us primarily. And in terms of where that investment is going, it's really across all the functions.

And if I think about R&D, it's super important for us to keep investing there as well because, unlike some companies, we don't view open source as a mechanism to outsource R&D to the community. In fact if anything we believe that we need to continue to maintain the pace of innovation and leadership there.

On the go-to-market side it's about expanding coverage and expanding the different routes to market that we have. And then as we scale in such a distributed way across the globe from a G&A perspective, we've got to be there to enable the business and make sure that the infrastructure is there for the business to scale. So it is really across all dimensions that we are continuing to invest in the business.

Great, thank you. And last question, just curious if you observed any type of acceleration either in the business or competitively given the IPO and just greater awareness.

Yes, I can take that. Not necessarily. I mean, the IPO obviously made us well known, but I would say that our open source roots and our broad adoption, we reported historically about the number of downloads and the number of users and customers that we have. That is exciting for us.

So the people that use our products know about us and that's the most important thing. And they know us, they use us and they get excited about the products and then they continue to use us and hopefully become our customers.

Richard Davis, Canaccord.

For firms at your stage of growth, a key to success is that well oiled sales machine and then the sales motion you can replicate. Do you believe you have that -- your numbers are good obviously, but do you believe you have that sales motion nailed down?

And could you just -- one of the things we see with companies like yours is where, if you are a salesman, do you start to engage with the prospect? Is there a certain size, or how do you titrate that so people don't run like rabbits all over the place to the wrong spots? Thanks.

Let me take that if I may. So first of all, we are humbled to have the very senior sales executives that we have in Elastic that have seen this level of growth and scale historically in their life. So they help us obviously make sure we don't only capture the opportunity that is in front of us, but also make sure that we implement the right foundational structures to grow correctly to capture the opportunity that is way ahead of us.

I think the best place it's reflected is in our geographical distribution of our sales force and also the fact that we've already implemented segmentation within the sales force. So these two aspects allow us to have multiple vectors of growth in hiring. And obviously couple that with multiple use cases and other factors in our open source distribution model, that makes it to a pretty unique and very exciting combination for us.

The other part I would say is -- and maybe that touches into the geographical and segmentation -- our goal is to engage with the customers at the point where they are already using us. We don't necessarily want to engage with customers when they don't -- haven't used us get. That is the whole point of open source and free distribution model.

But once they do, we will engage with a customer whether they are small or big, whether they have a small project or a large project that they start to use us. And we can use that in a more efficient manner thanks to the segmentation that we have within the sales force obviously.

The last thing I would say when it comes to the sales force, one of the challenges or mistakes that open source companies have done historically is that they've engaged with a developer over the first or second tier of engagement within their organization, but then that's the limit of their scale that they had.

We are building a sales force that can scale all the way up to talking to the CSO or CIO or C level executives and make sure that we can help them make a decision to implement Elastic across the whole organization. And we are implementing this tiered or segmented model to make sure that we address all of these aspects.

So, that's in a nutshell our sales go-to-market. And obviously that means that we have a lot of vectors to grow. And as you can see, we are investing heavily in that.

Got it. And then here's a simple question for Janesh. What is the fully diluted share count so that we can calculate enterprise value?

87.5 I believe when I last checked, but I'll confirm that. 87.5, yes.

And this will conclude our question-and-answer session. I would like to turn the conference back over to Shay Banon for any closing remarks.

Yes, thank you. Thank you all for joining the call. Q2 was a strong quarter for us and we look forward to seeing many of you at the Barclays conference later this week and continuing our momentum through the remainder of fiscal year 2019. Thank you all very much.

The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.