MongoDB, Inc. (NASDAQ:MDB) Q2 2021 Earnings Conference Call - Final Transcript
Sep 02, 2020 • 05:00 pm ET
as developers create enhanced applications that lead to a competitive advantage.
Since our inception 13 years ago, we put the developer at the center of our universe, and we introduced a new class of database based on the document model or JSON. JSON is a data format that's easy for developers to read and write and machines to parse. We have always believed that JSON is the best way to work with data.
As tech savvy companies around the world adopted the document model, the industry took note; first, Microsoft, then AWS and most recently, Oracle tried to emulate what we have done. Oracle recently made public statements that acknowledge that JSON has become the main data model for new applications and their developers love JSON because it provides support for dynamic schemas constantly making it easy to make changes. I believe it's noteworthy that the industry now agrees with our fundamental premise. The document model is simply the best way to work with data.
Our mission continues to make it stunningly easy for software developers to work with data wherever it resides to drive innovation and create value. At MongoDB.live, our user conference held in June, we made significant product announcements -- several significant product announcements that further advance our mission. With the introduction of MongoDB 4.4, we delivered a number of additional feature enhancements that push the envelope of what it means to be a modern database. With new capabilities in our query language layered on the most flexible distributed systems architecture anywhere, developers can build the most sophisticated transactional and analytical applications securely at scale.
MongoDB Atlas Data Lake is now generally available and allows teams to query and analyze the structured and unstructured data in the S3 buckets using the MongoDB Query Language. Atlas Data Lake also supports federated queries, which means teams can submit a single query and analyze operational data in Atlas alongside the data in S3.
We announced the beta of Atlas Online Archive, which completely changes the economics of large datasets by allowing users to define rules that automatically archive data from the Atlas database to low-cost cloud object storage. Best of all, customers retain the ability to seamlessly query their archive data with no extra effort.
The general availability of Atlas Search allows developers to deliver rich search experiences on top of their data in the cloud without needing to deploy, learn and manage a separate search technology. Atlas Search uses the MongoDB Query Language and is fully managed.
And finally, we unveiled MongoDB Realm. It combines the popular Realm Mobile Database we acquired last year and the serverless data access, data movement and data manipulation services for me, known as MongoDB Stitch. Our core component of MongoDB Realm is Realm Sync, which is available in public beta. This edge-to-cloud data synchronization service between Realm Mobile Database on the front-end and MongoDB Atlas on the back-end solves one of the most challenging data problems for mobile developers.
Our recent product announcements