JOINs and Aggregations Using Real-Time Indexing on MongoDB Atlas

PublishedJune 9, 2020

Do you want to build intelligent applications on your data in MongoDB Atlas without worrying about which fields to index and how to do aggregations and joins with other data sets? This session shows you how to use MongoDB Change Streams with Rockset for a real-time, interactive SQL experience so your apps can do search, aggregations and JOINs across MongoDB and other data sets. You can eliminate the need for client-side logic to combine MongoDB data with other data sources as you build intelligent applications and microservices at scale.

Come learn how Converged Indexing combines columnar, search and document indexes to offer low-latency queries. Rockset maps a JSON document into individual keys and values to be stored internally in RocksDB's log-structured merge (LSM) tree, allowing every field, including nested fields to be indexed. Rockset uses MongoDB's new Change Streams to keep the index updated continuously and in real-time. You can auto-index datasets from MongoDB Atlas, Kafka or S3 without writing a single line of ETL code. Rockset is serverless and provides SQL Query Lambdas as REST endpoints for millisecond-latency search, aggregations and joins at scale. MongoDB combined with Rockset is ideal for powering intelligent applications like personalization engines, gaming leaderboards, IoT apps and vision-AI based automation.

View Presentation

view presentation