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Reduce pauses.
Improve quality of service for Spark users and reduce infrastructure bottlenecks for IT by eliminating Java pauses, stalls, and stop-the-world failures.
“The Azul Platform performance is so superior that we’re now doing things with our big data system that cannot be done without Azul.”
The Renaissance benchmarks, where Azul Platform Prime outperforms OpenJDK by 37%, features key Chi Square test, logistic regression and random forest decision trees from Apache Spark.
Azul Platform Prime reduces infrastructure costs and improves performance of your big data stack, including Kafka, Cassandra, Spark, and Hadoop.
Forrester Consulting conducted a Total Economic Impact™ study to evaluate the return on investment of Azul Platform Prime based on customers’ actual results. The results were game-changing.
Reduce worst-case pauses from 34 seconds down to 35 milliseconds, facilitating larger heaps and allowing more DataNodes in your Hadoop clusters.
Azul delivers the turbocharged performance you need to handle the scale of Java-based big data while actually reducing your infrastructure requirements.