Eventador.io, the streaming data engine for building applications, is releasing an updated version of the Eventador Platform, tackling the complex problem of providing a queryable, time-consistent state of streams via materialized views.
Views are defined using ANSI SQL, are automatically indexed and maintained, and arbitrarily queried via RESTful endpoints. Users can query by secondary key, perform range scans, and can utilize a suite of common operators against these views.
“Companies have adopted Apache Kafka as the de facto data bus for streaming data,” said Kenny Gorman, co-founder and CEO of Eventador. “By using the Eventador Platform, customers no longer need to provision expensive, often slow database infrastructure and can instead query streaming data directly using materialized views. The Eventador Platform is a bespoke solution, not a simple add-on to Kafka, that solves the disconnect between streaming data and applications.”
With the new release, the Eventador Platform removes the need for additional database, web server, load balancing, or other complex infrastructure, which means developing streaming applications is now faster and less costly than with current, often piecemeal stream processing systems.
This not only provides organizations the lowest possible TCO for their streaming platforms but also increases innovation and access to new revenue streams with faster application time-to-market.
With Eventador, data science, developer, and data engineering teams can unlock new value and power from data streams in their models, applications, and ETL flows.
The Eventador Platform is a high performance, enterprise-grade engine for running continuous stream processing jobs.
Users can now materialize stateful and queryable views of data using ANSI SQL for use in applications, notebooks, machine learning models, and more.
For more information about this release, visit https://eventador.io/.