Imply 3.3 Improves Performance and Reduces TCO for Real-Time Intelligence

Imply has announced the release of a new version of its flagship product. Imply is a real-time analytics solution based on Apache Druid to store, query, and visualize event-driven data.

Founded by the authors of the Apache Druid database, Imply provides a cloud-native solution that delivers real-time ingestion, interactive ad hoc queries, and intuitive visualizations for event-driven and streaming data flows. The company has operations in North America, Europe, and Asia Pacific and is backed by Andreesen Horowitz, Khosla Ventures, and Geodesic Capital.

The Imply solution is used by organizations to deliver self-service analytics to their business users, make BI interactive and exploratory, and create data-driven applications for their customers, and the product update features enhancements to help customers optimize their analytics spend and improve time to insight on their freshest data, while extending Imply’s real-time analytics performance to a broader set of queries. 

In particular, according to the company, Imply 3.3 takes advantage of new SQL JOIN support in Apache Druid 0.18. The addition of JOIN operations broadens Druid’s performance advantage over data warehouses and data lake query engines by leveraging Druid’s architectural advantages such as advanced indexing and horizontal query distribution. This enables users to query multiple datasets directly using standard SQL operations while not sacrificing performance.

Support for JOIN operations reduces cloud data storage volumes and compute costs, and enables broad adoption of self-service analytics. Previously, multiple datasets would have to be “flattened” into a single table which included redundant data and made updates expensive. Now multiple datasets can be used “as is,” simplifying data pipelines and creating substantial savings by reducing storage costs, data ingestion costs and maintenance costs.  

“Digital transformation has spawned huge amounts of continuously flowing data. Our customers’ challenge is to bring that data to bear on day-to-day decisions, cost-effectively,” said Fangjin Yang, chief executive officer and co-founder of Imply, “Our latest release greatly improves the cloud computing economics of real-time intelligence, while maintaining best-in-class performance, so that companies can extend analytics beyond the analyst, to business users, while maintaining fiscal responsibility.”

In this product update, Imply has also added "query laning" to improve resource utilization and reduce costs. According to Imply, query laning works like an HOV lane, providing prioritized access to a subset of resources for urgent queries and ensuring that interactive time-sensitive queries are not blocked by longer-running reporting queries.

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