Gartner Report: Which Java Runtime is for you? | DOWNLOAD NOW


Increase Ignite capacity, reduce pause times & remove Java-caused limits to scalability.

Massive transactional, analytical & streaming workloads at petabyte scale? No problem.

Azul customers combining with Ignite dramatically speed up and add resilience for Java applications
in low-latency use cases, such as credit card authorization and payment processing.


Reduce stop-the-world pauses.

Consistently deliver 10x better latency for the 99.99th percentile in Ignite in comparison to general-purpose JVMs like HotSpot.


Deliver results in real-time.

Thousands of transactions per second—it doesn’t get any more real-time than that.


Scale out across RAM and disk.

Scale to Terabytes, and cache more for fastest performance and cache less to reduce infrastructure costs.

“The combined solution of GridGain’s in-memory computing platform and Azul Platform Prime eliminates garbage collection pauses, enabling, for example, processing thousands of financial transactions per second in the low milliseconds range while scaling to petabytes of data.”

Nikita Ivanov, Founder and CTO, GridGain

Ignite in-memory performance.

See benchmarks from a credit card payment system using the commercially supported version of Apache Ignite from GridGain alongside Azul Platform Prime.

Check It Out

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.

Explore Big Data with Azul

Read more about GridGain and Azul.

Running GridGain on Azul Platform Prime allows enterprises to increase the on-heap memory allocated on each GridGain node.

Read the Case Study

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

Forrester Consulting conducted a Total Economic Impact™ study to evaluate Azul Platform Prime’s TCO and ROI over three years. The results are pretty mind-blowing.

Read the Study

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.