MongoDB is a document-oriented database which means it works on principles of dealing with "documents"; it allows you to express data in its natural form, the way it's meant to be. Second, we expect to see a sequential decline in the EA business after a stronger than expected Q1. Operator? timestamps must be in ascending order. Also, no We have this very close value linkage, and so it maps quite tightly to the underlying application usage for our customers and their end users. Certainly, as roughly two-third of the business is Atlas and as I mentioned, about 80% of that does not flow through deferreds, but also what that means is that a larger portion of what will run through deferreds is EA. And then Michael, real quick. I apologize. First, I want to remind you that Q2 has three more days than Q1, which is a tailwind for Q2 Atlas revenue. In $setWindowFields, the windows are relative to each document, so the calculations are performed on each document. Install forever-mac; Copy server/mongodb-grafana-proxy.plist to ~/Library/LaunchAgents; run launchctl load mongodb-grafana-proxy from ~/Library/LaunchAgents; This launch ctrl plist runs the node script via forever. More information can be found at https://grafana.com/ Device Monitor Now turning to our results. MongoDB is a document-based general purpose database with flexible schema design and a rich query language. And so the demand for using MongoDB to build and run these AI apps is very high. And I had one follow-up for Michael. And beyond that, obviously, [indiscernible] is people value MongoDB's ability with a flexible document model. MongoDB is a general purpose document database that has native support for time series data. And so I will clearly say it wasn't AI that drove the acquisition of workloads. As you know, we will be facing very difficult EA compares throughout fiscal 2024, and Q1 was no exception as evidenced by our slower year-over-year EA revenue growth. Adjust the charts Data Source to use the same pipeline we did above: As a result, the data source exposes all fields such as symbol, date, close, and averageMonthClosingPrice, which can be used directly in a line graph: When charting this data, we can see the immediate value of this analysis: The graphs above show a closing price and a rolling 30-day average graph of each stock. It is spread over the duration. And we look forward to seeing you on June 22 at the Javits Center in New York City. The MongoDB plugin provides an editor where you can write/paste your MongoDB queries. Maybe, the first one on the consumption trends. Grafana is an open source software for time series analytics tool which will be used during this tutorial. Need for Monitoring of MongoDB Time series data is generated everywhere from social media to stock tickers to IoT devices. Now I'd like to spend a few minutes reviewing the adoption trends of MongoDB across our customer base. So you have talked about revenue being linked to consumption. In extreme cases, Grafana freezes. Third, we continue to expect that the year-over-year growth of Enterprise Advanced will be impacted by the difficult compares from the prior-year period. You can capture all of that. MongoDB Charts is a great tool to visualize the data calculated by the above aggregation pipeline. change the $symbol variable to a multi-value answer and make a slight That was the range that we've seen the performance in for Q1. Thank you taking my question and congrats on a great quarter. GE Healthcare's use of Atlas helps healthcare providers enhance productivity by reducing the complexity and time required to manage databases, resulting in an 83% decrease in data retrieval time and enabling faster deployment of IoT devices. In your query, replace time_bucket with time_bucket_gapfill. Strong start to the year, no major changes. If I could just follow up on Michael's last question there. So we don't have customers who are trying to move data off Atlas. Create, explore, and share beautiful dashboards that combine data from multiple sources to foster a data-driven culture within your team. Over the time since we've launched it, we've seen an 8 times increase in their end user consumption. Digital transformation is redefining how organizations operate, and MongoDB is helping customers on this journey by delivering the developer data platform that powers the migration from on-premises to the cloud. During their migration journey to Atlas, the company identified [indiscernible] significant infrastructure reduction and subsequent cost-savings. We're very excited about the prospects of relational migrator and helping to reduce the cost and time to migrate relational apps to MongoDB, but we're still early in that journey. You can read more on template variables with MongoDB in our documentation. When analyzed, the individual data pieces form a meaningful insight over a period of time. Lets look at a diagnostics kitchen sink dashboard, just to get an idea of the capabilities here. Thank you. And again, as I mentioned earlier, it's all about us acquiring high-quality workloads. And I appreciate you reiterating the difficult comps there, Michael. The extension of the deal, we initially signed a multiyear deal with them. I mean, are you at a point where the new customer momentum more than offsets declining consumption growth trends that you have better visibility into your business than you did probably, say, a year back, six months back? The key point, though, is that you still need an operational data store to store the actual data. In this step, you will build a dashboard to visualize your MongoDB data in Grafana. We remain laser-focused on our North Star, which is acquiring new workloads from both new and existing customers. The And when you think about the -- as I mentioned, there's a little bit of variability period to period, but other than sort of the start of the downturn in Q2 of last year and the more pronounced holiday slowdown, it's been in a fairly reasonable range. So what really drove the better-than-expected usage in 1Q? Note: By signing up, you agree to be emailed related product-level information. Turning to Enterprise Advanced. Learn more >. I think, if I can just follow up with a two parter, maybe more for Dev here, but first, I know that you're really citing the sharp execution from the go-to-market teams with respect to the number of new workloads or customer wins. So the more the apps are used, the more revenue that drives. I would not have forecast such high gross margins with Atlas at almost two-thirds of our revenue. As Dev mentioned, we continue to see a healthy new business environment, both in terms of acquiring new customers, as well as acquiring new workloads within existing customers. How many users visited a website page each day in the past week. We expect non-GAAP income from operations to be in the range of $36 million to $39 million and non-GAAP net income per share to be in the range of $0.43 to $0.46 based on 82.5 million estimated diluted weighted average shares outstanding. MongoDB provides a variety of aggregation pipeline operators and aggregation pipeline stages to enable developers to analyze data. Thank you. Yes. Our next question comes from the line of Mike Cikos of Needham. Thanks. value of your data. Grafana returns a graph that looks similar to this: In the previous example, you queried for all transactions of AMD stock in a 6 -hour period. This creates the long, straight, almost-horizontal lines you Well finance startups like Hugging Face, Tekion, One AI and [Nuro] (ph) are examples of companies using MongoDB to help deliver the next wave of AI-powered applications to their customers. It seems like Atlas has really been above your expectations in terms of the gross margin. A document can be added to a time series collection using any of the methods that can be used to insert documents into other MongoDB collections. Yeah. Therefore, users can use a single unified Query API utilizing MongoDB as a time series database alongside other database use cases. We are obviously continuing to invest for the long term, though, and believe that we can walk and chew gum at the same time. Our next question comes from the line of Kingsley Crane of Canaccord. Seems strange? Examples are weather measurement data and stock trading data. And so there's no real reason to change that outlook for the balance of the year. Great, blocking and tackling and walking while chewing gum. And then I've got a quick follow-up. We're very pleased with our gross margin progression, especially in the context of Atlas representing 65% of our overall business. Thank you. For example, let's drop our existing dowJonesTickerData collection and create a new one that has a metaField named "meta.". So those are the drivers and that's a big focus for us as well. Moreover, the shift to AI will favor modern platforms that offer a rich and sophisticated set of capabilities, delivered in a performance and scalable way. We also believe that many existing applications will be re-platformed to be AI-enabled. Please. This is an example of valid time-series data: If you are new to Grafana, see the Grafana tutorials Step 1: Creating a time series collection The command to create this new time series collection type is as follows: db.createCollection("windsensors", { timeseries: { timeField: "ts", metaField: "metadata", granularity: "seconds" } } ) Obviously there's the China Mobile case study or vignette that Dev walked through, and you can always find those in every quarter. Sorting is typically part of the aggregate pipeline. Instead of the metaField being a single value (e.g., symbol), update the metaField to be an object that contains multiple pieces of metadata. Congratulations on the quarter, great start to the year. Thank you. Dev, if you -- everyone talks about AI at the moment and Mongo in theory always kind of view as an operational database. Organizations, including Anywhere Real Estate, GE Healthcare and Intuit are leveraging the power of our developer data platform. But why did we see that sequential decline in deferred revenue that we haven't typically seen? And then [Multiple Speakers] in terms of expectations for the rest of the year? Our next question comes from the line of Brad Reback of Stifel. You can create a new time series collection with the createCollection() command. China Mobile provides mobile voice and multimedia services via its nationwide mobile telecom network across Mainland China and Hong Kong. That's not a phenomenon that we see. And I just think it's important to understand that because you can see the slower growth rate on EA shining through in Q1. Similar to $group, $setWindowFields allows you to apply one or more operations on a defined window. graph makes it easy to see if the value of a stock is going up or down. It now appears that you have a cadence where you -- despite challenging consumption trends on a per-customer basis, you've been able to add new customers at record pace, so results have been actually quite resilient. time range, it might take a long time for Grafana to get all the rows and While not all data is time series in nature, a growing percentage of it can be classified as time series. Grafana Cloud timestamp, mongodb srvajpe November 28, 2022, 12:26pm 1 I have data for every millisecond stored in MongoDB. So it's really tied to the product market fit of those companies, but the general trend that we are very pleased about is that, there's a lot of people leaning towards MongoDB in terms of thinking about the next set of AI apps that they're building. Okay. Or is it hard to call bottom on the per-user consumption level? Yes. [0, 1, 2, 3, 4]). Hi everyone. Thanks. In this article, you'll learn what time series data is, how you can store and query time series data in MongoDB, and what the best practices are for working with time series data in MongoDB. Powered by Discourse, best viewed with JavaScript enabled. What your Grafana - Prometheus - MongoDB exporter will look like; How to install Prometheus, a modern time-series database on your computer; How to configure import a MongoDB dashboard in seconds; How to set up the MongoDB developed by Percona as well as binding it to MongoDB; Yes. The date field is in MongoDB Date format and when plugged into Grafana it is losing millisecond precision. So that, what drove the outperformance of that was stronger underlying usage of those applications, right? So I want -- maybe explain it, but I'm not sure. This concludes today's conference call. Downloads. Step 3 Building a MongoDB Dashboard in Grafana. And third, because of the breadth of our platform and the wide variety of use cases we support that becomes even more of an impetus to use MongoDB. Second, we continue to expect that Atlas consumption growth will be impacted by the difficult macro environment throughout fiscal 2024. In addition, Q1 benefited from the timing of marketing programs, internal events and other expenses, which we now expect to incur later in the year. And is there any follow-through on that, Alibaba? As a reminder, our direct customer count growth is driven by customers who are net-new to our platform as well as self-serve customers with whom we've now established a direct sales relationship. And when we look at where we are now and the outlook, I think that's the right view, so I don't think that there's any particular data that would point to things suddenly becoming better or becoming materially worse. Yes. We can do that! I'm Grot. I wanted to start off -- just a question on the environment. OK, let's look at some time series data! Okay, just -- yes. When you work with time series data, you are often not only concerned with storing the data but also require high read and write performance and advanced query capabilities. of 24h. but doesn't connect the values over the weekend. I tried converting Date () to integer format and still facing the same problem. I think people understand that. extra calculations are needed to make the graph. Okay. Our new MongoDB data source plugin unlocks all of the data stored in MongoDB including diagnostic metrics for monitoring MongoDB itself for Grafana visualization, exploration, and alerting.. Good evening. Say the last part of the question again, Michael. MongoDB supports the idea of "Compound Variables", which enable you to use one variable as multiple variables to perform complex multi-key filters. Thank you. So like these are pretty good signs that customers are still prioritizing innovation and they're doing so leveraging modern platforms like MongoDB. Is this happening to you frequently? And Q1 tends to be a seasonally slower quarter for new EA business. Why use MongoDB and Grafana? In other words, their spend on our platform is directly aligned with the usage of their underlying application, therefore, the value they derive from it. Thank you for taking the questions and congrats to the MongoDB team on a strong start to the year. To us, this is confirmation we remain a top priority for our customers and that our value proposition continues to resonate even in this market. Finally, retention rates remained strong in Q1, reinforcing the enduring value in our platform. Hi. And again -- so that drives us to go acquire more workloads, high-quality workloads, that we can then onboard quickly. Each document contains the average closing price per month for a particular stock. My first question before I have to follow-on -- follow-up question. Great, yes. That drove more consumption and so that's what drove the outperformance. We have a high degree of existing customers who are engaging with our field organizations on AI use cases. Note that the non-GAAP net income per share guidance for the second quarter and full year fiscal 2024 includes a non-GAAP tax provision of approximately 20%. With that, I'd like to turn the call over to Dev. Our revised full year revenue guidance continues to assume consumption growth that is in line with the average consumption growth we've experienced since the slowdown began in Q2 of last year. Thank you and congrats from me. It These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions that could cause actual results to differ materially from our expectations. And one for you, Michael. Open positions, Check out the open source projects we support We have not seen that trend. SELECT time_bucket_gapfill('$bucket_interval', time) AS time, GROUP BY time_bucket_gapfill('$bucket_interval', time), Create multiple time-series graphs in a single panel. - tgogos Sep 14, 2017 at 15:32 1 the default panel type. Quickly search through all your logs or stream them live. And I'm just curious, from your perspective, how you see this playing out. Thanks. And so that's just a very different dynamic when you start thinking about less from the income statement but more kind of away from the other parts of the balance sheet and some of the other calculations that you all do. I have a mongodb collection with 2 arrays per document. It continues to be a healthy part of the business, but I wouldn't uniquely call that out as sort of particularly driving the results, although it's obviously a big part of our long-term market opportunity. It was really sharp execution by go-to-market teams. So when you think about the underlying queries, right, the reads and writes of those applications, more activity. Other In other words, our usage growth assumptions for the remainder of the year remain unchanged from what we provided our initial guidance range for fiscal 2024 last quarter. Another example could be how a connected weather measurement device might obtain telemetry such as humidity levels and temperature change to forecast weather. And consequently, when apps are used less, the less revenue we get. Learn how to store and analyze your time series data using a MongoDB cluster. The recommended way to automatically delete expired data is by setting a TTL, Time To Live expression, on a time series collection in the form of an expireAfterSeconds parameter. We have not changed our outlook for the expected growth over the balance of the year. We talked about the China Mobile example where it was a very, very large workload servicing a very, very large user population. That's part of what led to the early renewal and extension given the success of the joint offering. Use time series collections with time series data when possible. Atlas now has -- about 80% of Atlas does not flow through deferred. For example, you can consume time series data to perform calculations using aggregation pipelines and plot graphs on the application side, via MongoDB Charts. In our case, we will create a secondary index that allows for efficient searching of both symbol and company. MongoDB added native support for time series data in version 5.0, making it even easier, faster, and cheaper to work with time series data. I appreciate the comments, Dev. Let me provide some context on Atlas consumption in the quarter. We have really focused our teams to acquire workloads either through the acquisition of new customers or the acquisition of workloads in existing customers. "FRAME" and "NOSE_Y". To solve this problem, you can pre-aggregate your data using TimescaleDB's Visit the official MongoDB documentation on aggregation pipeline operators to learn more about all of the available operators. Prior to version 5.0, MongoDB had a suggested data model for time series data. This further strains And so that's great to see. Awesome. Additionally, it could monitor air pollution to produce alerts or analysis before a crisis occurs. It's a much more graceful migration than having to replatform on to another technology when they want to move that workload to the cloud. It seems a little too early for Gen AI to be driving the number of new workloads, so what drove that [indiscernible] as well? I would now like to turn the conference back to Dev Ittycheria for closing remarks. It could be for cost reasons. That's great. time_bucket hyperfunction. In Grafana, create a new panel and add this query: Enter AMD in the symbol variable. But as the user numbers increase, performance degraded. Moreover, it provides more flexibility, as fields can vary from document to document and data structure can change over time as well. Q1 consumption was ahead of our expectations but remains below the levels we saw prior to the macro slowdown that began last year. Thank you. Right away you might have noticed movie production steadily increased then dropped off after 2014. Our next question comes from the line of Sanjit Singh of Morgan Stanley. I - What You Will Learn II - MongoDB, Grafana and Prometheus Architecture III - Installing The Different Tools a - Installing Prometheus b - Installing the MongoDB exporter c - Enabling MongoDB authentication So what would maybe explain it? To summarize, AI is just the latest example of the technology that promises to accelerate the production of more applications and greater demand for operational data stores, especially the ones best suited for modern data requirements such as MongoDB. After the speaker presentation, there will be a question-and-answer session. Requirements This plugin has the following requirements: A MongoDB instance with at least one user One of the following account types: Grafana Cloud: Pro customers, Advanced customers, or Pro trial users with the Enterprise plugin add-on enabled MongoDB's developer data platform continues to gain momentum as customers across industries and around the world are running their mission-critical projects on Atlas. Said another way, if you are slow, then you're obsolete. If we just assume a one year contract, which most of our contracts are, you'll get the same revenue over the time, but with the enterprise license -- enterprise events license, you'll see that upfront revenue being lumpier, right? To plot multiple time-series graphs in a single That's part of the reason why we talk about and go to great pains to explain the EA compares and some of those other things. A time-series graph is a line graph that plots points changing over time. We're not assuming things get materially worse, and we don't have any data that would suggest either of those directions. Our six figure customer count grew 28% year-over-year and our Atlas growth was 40% year-over-year. And so, that's going to happen over the long term and so that's something that's a trend that we're feeling good about. A leader in the HR and job finding tech space shifted from MongoDB Community to MongoDB Atlas during its journey to migrate its entire infrastructure from on-premises to the cloud. So I would like to ask a question about the replacement opportunity and in just a slightly different way. I wouldn't particularly call out a particular spike up. Hi, guys. To ensure this doesnt happen in the future, please enable Javascript and cookies in your browser. Is it fair to assume that, in next couple of quarters, consumption level may reset at a new normal and then maybe resume growth from that level? So we are seeing -- again, part of acquiring a workload is acquiring a relational workload and replatforming it on MongoDB, so when we say acquiring a workload, you should not always assume it's a new workload. You should also include the following options: Lastly, you may want to include this option if you would like to remove data after a certain time has passed: The following example creates a time series collection named dowJonesTickerData where the timeField is date and the metaField is symbol: Each document that you add to the time series collection will need to specify at least the timeField. That was what was included in our guide and that's what's initially for fiscal 2024. Another option for handling old data is to tier it into operational and online archive storage.You can use Atlas Online Archive to automatically archive data from your Atlas cluster to a MongoDB-managed Data Lake. Some of those includes some very cutting-edge well-financed startups like Nuro and Hugging Face and Tekion. First, I'll start with our first quarter results. The dashboard in examples\Sensor Values Count - Atlas.json shows this.. Running the proxy as a service on a Mac. Dev, last quarter you talked about a couple of very large financial institutions beginning to migrate, I believe it was hundreds of apps. Prometheus , (time series database). MongoDB is an essential platform in this drive for innovation, making us the critical investment priority. In this case the datasource is Prometheus not mongodb . But first, you need rows containing null values wherever you have See the official MongoDB documentation on configuring online archives for more information. We ended the quarter with 1,761 customers with at least $100,000 in ARR and annualized MRR, which is up from 1,379 in the year-ago period. Below is an example document that resulted from running the above aggregation. Moving on to Atlas consumption trends. And we do that not just from our sales organization but also from our self-serve business. And so I think the key thing when you compare it to the 606 implications particularly of enterprise advanced and the term license revenue is, while it's not ratable -- and I do think sometimes there's the tendency to confuse it was ratable. And maybe how you're preparing your go-to-market team to tackle that opportunity. Michael will share more detail on this. Yes. Mike, if we could unpack the 2Q guide a little bit. You will see this impact in other subscription revenues, the portion that is neither Atlas nor EA. Thank you. That's the first part. All right. And I believe that over time, people will gravitate to a more seamless and integrated platform that offers a compelling user experience. Yes. This could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market, and . We look forward to telling you more at our Investor session on June 22. MongoDB allows you to store and process time series data at scale. Your question please, Howard. If they're not doing well, then obviously they're not going to drive a lot of consumption. Please disable your ad-blocker and refresh. It's usually plotted in And we had a record number of new workloads added this quarter from existing customers. In addition, it is frequently updated, and devops friendly. This includes China Mobile, Tata Digital and Grant Thornton International. Your question please, Mike. A time series database (TSDB) is a database optimized for time-stamped or time series data. But first, I would like to personally invite all of you to the Investor session at MongoDB.local New York City to be held at the Javits Center on June 22. Time series data is any data that is collected over time and is uniquely identified by one or more unchanging parameters. With this plugin, we can quickly identify anomalies in data, and even add alerting so we get notifications when something strange occurs! And so we've continued to execute incredibly well there. It sounded like from what you guys are saying that you guys are executing well, but things are still pretty tight from a budget environment perspective. Thinking about a long-term opportunity, I feel exceptionally confident about our core underlying growth driver, the need for companies to use software as a competitive advantage. As I've said many times in the past, a durable competitive advantage is built through custom software, it cannot be obtained with an off-the-shelf product. At this time, all participants are in a listen-only mode. Gross profit in the first quarter was $279.9 million, representing a gross margin of 76%, which is up from 75% in the year-ago period. I just wanted to ask about the linearity of consumption through the quarter and then any comments you have on consumption in the month of May? Or is it truly onetime 2Q? Since the year got off to such a great start here, does it impact your hiring plans for the rest of this fiscal year? Weve thrown a lot in here. Your question please, Fred. A better alternative is to There's got to be some compelling event for a customer to do so. And there are some adjunct solutions out there that have come out that are bespoke solutions but are not tied to actually where the data resides, so it's not the best developer experience. This returned approximately 3 800 data points. We generated revenue of $368 million, a 29% year-over-year increase and above the high-end of our guidance. The set will contain the same number of documents as the original collection. sign up now for a free 14-day trial of Grafana Cloud Pro, Observing and visualizing your MongoDB Data. row with a null value wherever there is no data. That's great. Therefore, our starting Atlas ARR for Q2 is higher. One, billings in general is not a super helpful metric for us. It bridges the less-than-24-hour gap between 4:00PM and 9:30AM, And that's it for me. So wanted to get your sort of latest perspective on whether you see cloud spend and optimization headwinds fading anytime soon? How do you fit into this kind of new AI world? Starting in MongoDB 5.0 there is a new collection type, time-series collections, which are specifically designed for storing and working with time-series data without the hassle or need to worry about low-level model optimization.
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