Azul Introduces Code Inventory The Solution That Identifies Unused and Dead Code for Removal in Production, Saving Developer Time and Money 
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Consistently improve Apache Spark and Scala response times

Faster Spark response times.
More infrastructure savings.

Across most query types, Azul Platform Prime delivers 24% to 100% better response times.
This reduces infrastructure overhead and provides more opportunities for machine learning, streaming, and event-based anomaly detection use cases, such as fraud and intrusion threat detection, environmental monitoring, and trading.

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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.

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Deliver event-based machine learning analytics for faster results.

Spark delivers a 24% improvement in raw speed with Azul Platform Prime’s Falcon Compiler.

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Fewer pauses and faster streaming means infrastructure savings.

Meet your Spark and big data Scala SLA targets with fewer cloud instances and/or fewer servers.

 

“The Azul Platform performance is so superior that we’re now doing things with our big data system that cannot be done without Azul.”

Ariel Pisetzky, VP of IT
Forest decision trees from Apache Spark

See Spark Machine Learning Library Benchmarks

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.

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Explore big data technologies with Azul.

Azul Platform Prime reduces infrastructure costs and improves performance of your big data stack, including Kafka, Cassandra, Spark, and Hadoop.

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The Total Economic Impact of Azul Zing eBook by Forrester

224% ROI over 3 years and payback in under 3 months for Azul Platform Prime.

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.

Read the Study
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Increase Hadoop cluster sizes with expanded NameNodes.

Reduce worst-case pauses from 34 seconds down to 35 milliseconds, facilitating larger heaps and allowing more DataNodes in your Hadoop clusters.

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Azul powers the modern cloud enterprise.

Azul delivers the turbocharged performance you need to handle the scale of Java-based big data while actually reducing your infrastructure requirements.