The News: MongoDB had its 9th annual MongoDB World event this week and launched a raft of updates and new features across its entire portfolio including the flagship MongoDB V6 database and Atlas offerings. Check out the full details of the of new features and enhancements released at MongoDB World 2022 here.
MongoDB World – MongoDB Going All in on the Cloud and Platform
Analyst Take: I have been going to MongoDB World events for the last few years now and the event I attended earlier this week is the largest and widest scope of any that I have attended previously. MongoDB started out with a simple mission – to disrupt the established player in the SQL database marketplace, namely Oracle. The company today has a much wider mission than purely databases and is focused on what it calls the Developer Data Platform.
Dev Ittycheria, CEO and President of MongoDB took to the stage on Tuesday morning and delivered a compelling keynote on the direction of the company and the adoption of the company’s offerings. According to Ittcheria, MongoDB has been downloaded 265m times and the company is touting 35,000+ customers. These are impressive numbers. .During his presentation, Ittycheria outlined why he believed this adoption was happening, put simply the reason is “developer productivity = remove friction working with data.”
MongoDB is focused on enabling development teams to innovate with more increased velocity servicing more of the data lifecycle, beyond the original focus of just databases, optimizing for modern architectures, including an increased focus on the public cloud, and implementing the enhanced data encryption — all within a single integrated developer data platform. Oftentimes the hardest task developers face is dealing with state and, as a result, the original appeal of MongoDB was designed to give developers an easier way to store, index, and retrieve documents as objects or documents, rather than translate this work to traditional SQL models.
“Hundreds of millions of new applications will be developed over the coming years that deliver compelling customer experiences, enable new capabilities to transform businesses, and increase operational efficiency via more sophisticated automation – and these applications all require a highly scalable, cloud-native, globally distributed data platform,” said Dev Ittycheria, CEO and President of MongoDB. “Our vision is to offer a developer data platform that provides a modern and elegant developer experience, enables broad support for a wide variety of use cases, and delivers the performance and scale needed to address the most demanding requirements.”
At MongoDB World, MongoDB announced a series of updates, including the addition of querying encrypted data without having to decrypt it first, columnstore indexing, and a new SQL interface. However, my major takeaway here was the breadth and scope the company is now looking to address with what it describes as its “Developer data platform.”
Mark Porter, MongoDB’s recently appointed CTO, outlined in his main stage presentation that he believes the scope of the announcements made at MongoDB World represents the culmination of the last few years of work for MongoDB. While the company started out as a pure database provider that was bringing a new type of architecture to the market, in recent years the company has pivoted to build out the capabilities around this core database offering and add features like integrated search, acquiring mobile application development platform Realm, launching the Atlas data lake service, and more.
The Company is focused on pulling all these functions together into a developer data platform while leaving them composable, standards-based, and pulling them all together into a developer-focused toolkit, enabling developers to focus on writing modern applications.
The discussion at MongoDB World this week is the first time I’ve heard the company talk about this breadth of scope as a cohesive platform. While ‘platform’ is the new industry buzzword, especially for fast-growing companies looking to break out of the ‘mono-product’ category and expand their multiples, I do believe MongoDB is onto something.
MongoDB’s Strategy is to Focus on Wider Use Cases
MongoDB is, I believe, a solid one. The company is looking to extend its reach to data use cases beyond operational and transactional scenarios and to ultimately serve search and analytics use cases, all within a unified platform. These enhancements allow teams to accomplish more while preserving a consistent developer experience and reducing the complexity of the data infrastructure required to support modern applications.
MongoDB announced a variety of capabilities during MongoDB World designed to make it easier for developers to leverage in-app analytics and deliver enhanced application experiences. The main headliners were:
Column Store Indexes – MongoDB columnstore indexing is designed to help developers build analytical queries into their applications. The feature is architected to enable developers to create a purpose-built index to accelerate analytical queries without requiring any changes to the document structure or having to move data to another system.
The functionality becomes available later this year, and will enable users to create and maintain a purpose-built index that increases the speed of many common analytical queries without requiring any changes to the document structure.
MongoDB is claiming the feature changes the game in terms of performance in the database for certain types of queries. According to numbers shared during the event, the company is apparently seeing anywhere from a 5x to a 200x query improvement for certain kinds of complex analytical sort of queries. MongoDB’s architectural approach is that analytics nodes can now be scaled separately, allowing teams to independently tune the performance of their operational and analytical queries without over or under-provisioning.
MongoDB time series collections – This new feature set is designed to make it easier, and faster to build applications that monitor physical systems, track assets, or deal with financial data. In the MongoDB 6.0 release, time series collections support secondary indexes on measurements, and feature read performance improvements and optimizations for sorting time-based data more quickly.
In MongoDB 6.0, time-series collections can have secondary indexes on measurements, and the database system has been optimized to sort time-based data more quickly. Although there are a number of databases specifically geared towards time-series data, such as InfluxDB, many organizations may not want to stand up an entire database system for this specific use, which would be a separate system costing more in terms of support and expertise, Davidson argued.
Atlas Search – Focusing on enabling fast and easy ways to build relevance-based search capabilities into applications, Atlas Search enables developers to rapidly build search experiences that allow end-users to frictionlessly browse, narrow down or refine their results by a number of different dimensions. As customers build more and more sophisticated apps, the complexity of the underlying data architecture has become increasingly complex to manage. Atlas Search, available in the DBaaS system, is designed to help developers avoid using Elasticsearch or Solr Search outside the core database. The company was keen to highlight the desire to deliver rich experiences of interaction while removing the complexity of having a dedicated search-engine side by side with a MongoDB database.
Servicing More of the Data Lifecycle
I felt that some of the biggest news coming out of MongoDB World was the expansion of MongoDB’s ambitions beyond its traditional addressable market of databases — whether they are on-premises or in the cloud. While the company was not explicit about picking a fight with Snowflake, the intentions here were clear. I spoke with a senior member of the competitive research team and he shared that the company actively tracks and compares its offerings against key players and that that list also include Snowflake, especially so after the company’s recent Data Lake announcements.
Focusing on the developer, MongoDB announced new capabilities that look to enable development teams to more rapidly and with less friction analyze, transform, and move their data in Atlas. The company was also keen to stress that the architecture of the Developer Data Platform would reduce the reliance on batch processes and Export Transform Load (ETL), jobs that are friction points in legacy architectures and can lead to reduced developer velocity, delays in digital transformation projects, impose limits on productivity, and thus, lead to increased costs.
Atlas Data Lake – Ittycheria announced Atlas Data Lake in his keynote and let the audience digest the competitive implications of the announcement without explicitly referring to Snowflake, although it wasn’t hard to make the connection. Atlas Data Lake will allow for fully managed storage capabilities which, according to MongoDB, provide the economics of cloud object storage while optimizing for high-performing analytical queries. The ‘better together story’ the company is using as it relates to MongoDB Atlas databases is that Atlas Data Lake reformats, creates partition indexes, and partitions data as it is ingested from Atlas databases, creating a highly performant companion data lake. There wasn’t any benchmark or performance data shared to back up these claims, and I’ll be interested in tracking the developments here, as well as watching for comments from Snowflake in the event the company reacts to MongoDB’s announcements.
Security, Security, Security with Enhanced Data Encryption
Data breaches, leaks, and high-profile hacks are the new normal, and while we might collectively be increasingly desensitized to their impact, very real financial risks and impacts remain. As such, tools that minimize the illicit flow of sensitive personal data are in demand. In 2021, MongoDB acquired encryption specialist Aroki Systems and technology from the acquired company is set to become available for preview in MongoDB 6.0.
MongoDB argues that this marks the first time a database offers this capability, which goes beyond most existing encryption solutions that encrypt data in transit and at rest, but not when in use. In addition, MongoDB argues, it also put the burden on developers to understand cryptography. Mark Porter addressed this in his keynote, stressing that this is not homomorphic encryption, the prevailing technology for building similar features.
MongoDB announced Queryable Encryption, a feature that will allow database users to search their data while it remains encrypted. The tool, debuting in preview as part of the latest release, attempts to bridge academic cryptography findings and real world environments so users can adopt the feature without needing advanced theoretical expertise. Most interestingly, Queryable Encryption is architected to work with existing databases rather than requiring users to rearchitect their systems before they can take advantage of it.
Institutions ranging from businesses to governments, to health care facilities, and critical infrastructure already lean on encryption to render data unintelligible when it’s travelling across networks or sitting in storage, namely in-flight and at-rest. However, these approaches don’t protect data when it’s actively being used for legitimate reasons. This approach is gaining traction under the moniker of Confidential Computing. This end-to-end client-side encryption uses novel encrypted index data structures, the data being searched remains encrypted at all times on the database server, including in memory and in the CPU. MongoDB’s Queryable Encryption allows data to remain encrypted on the database, including in memory and in the CPU, while keys never leave the application and cannot be accessed by the database server.
Speed is a challenge in encrypted operations, where every extra key check and computation add complications to basic operations. MongoDB claims that searches performed with Queryable Encryption are performant — a claim that customers will be able to test for themselves with the new preview. MongoDB is also open sourcing much of the Queryable Encryption system so that users and other researchers can vet the underlying cryptography which I find encouraging.
At MongoDB World in 2016, the company released MongoDB Atlas, the company’s database as a service to run MongoDB in the Cloud, initially on AWS. MongoDB Atlas now also runs on Azure and GCP.
Six years later, Atlas has become the majority of the company’s revenue. In Q1 FY23 (ending in April), Atlas grew +82% Y/Y, and Atlas now represents 60% of the company’s top line. If you contrast this with FY20, Atlas represented only 39% of top line revenue. As such, it was no surprise that MongoDB announced updates to Atlas at the event.
The search feature of Atlas, powered by the open source Apache Lucene, has been enhanced to allow users to better browse and refine their results in different dimensions by way of a new feature called Search Facets, which implements an inverted index technology.
Device Sync – A new feature called Atlas Device Sync connects a fully managed backend database in Atlas to MongoDB’s popular mobile object database, Realm, which MongoDB acquired in 2019, granting granular control over the data synced to user applications. MongoDB’s new Flexible Sync option grants granular control over the data synced to user applications with intuitive language-native queries and hierarchical permissions.
C2C Sync – Cluster-to-Cluster Synchronization provides the continuous data synchronization of MongoDB clusters across environments whether in Atlas, in private cloud, on-premises, or on the edge. Cluster-to-Cluster Synchronization allows users to easily migrate data to the cloud, create test environments, create dedicated analytics environments, and support data residency requirements. This new functionality sets the stage for using data in multiple places for testing, analytics, and backup. The ability for customers to leverage Cluster-to-Cluster Synchronization (C2C) for many existing MongoDB-based applications is something they been wanting for a long time. This functionality will improve many facets of the software lifecycle, such as supporting “blue/green” deployments, data distribution, cloud migration and further increasing our high levels of geographic availability.
Data API – MongoDB’s Data API is a secure API for accessing Atlas data over HTTPS without any operational overhead. This provides developers a way to easily extend Atlas data into other apps and services in the cloud or into their serverless architectures.
While MongoDB Atlas aims to make databases easier to manage through a cloud delivered as-a-service model. The company now has an even easier option, Atlas Serverless, which is now generally available, and which removes the task of database provisioning and scaling altogether.
Atlas Serverless – In addition to supporting a wide range of workloads, organizations need to have the flexibility to deploy the right application architectures to accommodate their needs, increasingly this means a serverless architecture. Atlas Serverless is now generally available in MongoDB 6.0 and allows users to support a wide range of application requirements with minimal configuration and ongoing capacity management. Customers benefit from the ability to scale to zero and deploy in AWS, Azure, and GCP, and tiered pricing automatically reduces the cost for large workloads without upfront commitments.
MongoDB’s Vercel Partnership
Guillermo Rauch, CEO and Founder of Vercel took to the stage as part of the main keynote at MongoDB World to announce that MongoDB is launching a new integration with the Jamstack startup this week. The partnership will allow developers to more easily use MongoDB as the database to build websites and applications on top of Vercel’s platform. While people have obviously built similar integrations in the past, the level of alleged intimacy and elegance is intended to be the key takeaway, with both companies working on their products to enable a better developer experience.
The Vercel integration will allow teams using Vercel’s platform to develop, preview, and ship websites and applications to more easily get started with MongoDB Atlas as their backend database. Using Vercel’s Integrations Marketplace, developers can now deploy new web experiences on Atlas with zero configuration and instantly start building with documents that map directly to their code.
Looking Ahead for MongoDB
Looking ahead for MongoDB, the focus of the company is still about catering to developers, and for the company to deliver on its aspirations to go upmarket to the enterprise and to truly be front of mind for the C-Suite. To accomplish this, MongoDB must focus on broadening its audience to traditional database professionals. That said, the company’s messaging around the Data Developer Platform is encouraging.
The limitations of the relational database architecture are well documented and MongoDB is clearly positioning itself as the alternative. Going further, the proliferation of point solution databases has created a fragmented developer experience and led to a level of complexity in the data architecture with multiple data silos and higher costs in order to manage and support. MongoDB positioning itself as one single solution certainly has merit.
Where I struggle is the sheer breadth of the surface area that MongoDB now wants to address. The 70 competitors that MongoDB wants to compete with are, in some cases, high growth hot companies such as Snowflake, or heavily incumbent companies such as Oracle and IBM, and the competition here for the company is steep. I will be watching in the months ahead to see MongoDB reporting on customer adoption around the Developer Data Platform and look forward to watching the competitive landscape is evolving.
Disclosure: Futurum Research is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum Research as a whole.
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Image Credit: MongoDB
The original version of this article was first published on Futurum Research.
Steven Dickens is Vice President of Sales and Business Development and Senior Analyst at Futurum Research. Operating at the crossroads of technology and disruption, Steven engages with the world’s largest technology brands exploring new operating models and how they drive innovation and competitive edge for the enterprise. With experience in Open Source, Mission Critical Infrastructure, Cryptocurrencies, Blockchain, and FinTech innovation, Dickens makes the connections between the C-Suite executives, end users, and tech practitioners that are required for companies to drive maximum advantage from their technology deployments. Steven is an alumnus of industry titans such as HPE and IBM and has led multi-hundred million dollar sales teams that operate on the global stage. Steven was a founding board member, former Chairperson, and now Board Advisor for the Open Mainframe Project, a Linux Foundation Project promoting Open Source on the mainframe. Steven Dickens is a Birmingham, UK native, and his speaking engagements take him around the world each year as he shares his insights on the role technology and how it can transform our lives going forward.