Imply Launches Polaris, a Cloud Database Service for Modern Analytics Apps

Imply, a company founded by the original creators of Apache Druid, has announced the first milestone in Project Shapeshift, the 12-month initiative designed to solve the pressing issues developers face when building analytics applications. The announcement includes a cloud database service built from Apache Druid and the private preview of a multi-stage query engine for Druid.

According to Imply, developers are increasingly at the forefront of analytics innovation. Applications fueled by the digitization of businesses are being built for real-time observability at scale for cloud products and services, next-gen operational visibility for security and IT, revenue-impacting insights. and recommendations and for extending analytics to external customers.

Apache Druid has been the database of choice for analytics applications trusted by developers more than 1,000 companies including Netflix, Confluent, and Salesforce, accpording to Imply.

“Today, we are at an inflection point with the adoption of Apache Druid as every organization now needs to build modern analytics applications,” said Fangjin Yang, CEO and co-founder, Imply. “This is why it’s now time to take Druid to the next level. Project Shapeshift is all about making things easier for developers, so they can drive the analytics evolution inside their companies.” 

As developers turned to Apache Druid to enable interactive data experiences on streaming and batch data with limitless scale, Imply saw opportunity to simplify the end-to-end developer experience and extend the Druid architecture to power more analytics use cases for applications from a single database.  

Imply Polaris is a cloud database service built from the ground up to simplify the developer experience for analytics applications end-to-end. Much more than cloudifying Apache Druid, Polaris drives automation and intelligence that delivers the performance of Druid without needing expertise, and it provides a complete, integrated experience that simplifies everything from streaming to visualization.

Polaris introduces:

  • Fully-Managed Cloud Service: Developers can build modern analytics applications without needing to think about the underlying infrastructure. No more sizing and planning required to deploy and scale the database. Developers can start ingesting data and building applications in just a few minutes.
  • Database Optimization: Developers get all the performance of Druid they need without turning knobs. The service automates configurations and tuning parameters and includes built-in performance monitoring that ensures the database is optimized for every query in the application. 
  • Single Development Experience: Developers get a seamless, integrated experience to build analytics applications. A built-in, push-based streaming service via Confluent Cloud and visualization engine integrated into a single UI makes it simple to connect to data sources and build rich, interactive applications. 

Imply has also introduced a private preview of a multi-stage query engine.

The multi-stage query engine—in conjunction with the core Druid query engine—will extend Druid beyond interactivity to support the following new use cases in a single database platform:

  • Druid for Reporting: Improved ability to handle long-running, heavyweight queries to give developers a single database for powering applications that require both interactivity and complex reports or data exports. Cost-control capabilities make these heavyweight queries affordable.
  • Druid for Alerting: Building on Druid’s longstanding capability to combine streaming and historical data, the multi-stage query engine enables alerting across a large number of entities with complex conditions at scale.
  • Simplified and More Capable Ingestion: Druid has always provided very high concurrency—very fast queries across large data sets. Using the same SQL language that Druid already supports for queries, the new multi-stage query engine enables simplified ingestion from object stores, including HDFS, Amazon S3, Azure Blob and Google GCS with in-database transformation, making data ingestion easy without giving up any of Druid’s power to enable interactive conversations in modern data analytics applications. 

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