Java Technology Stack

Improve carrying capacity, eliminate memory bottlenecks, and reduce your infrastructure footprint by as much as 50%.

Reduce your infrastructure at least 20% while running Kafka 30% faster, with increased throughput and consistent, jitter-free performance.

Increase throughput on over 40% less infrastructure, and reduce median pause times.

Cut response times for Elasticsearch for the 75th to 99th percentiles by more than 75% without changing a single line of application code.

Expand NameNodes to handle more HDFS metadata, deliver larger HDFS clusters, and reduce infrastructure costs and operational complexity.

Improve Spark response times by 24% to 100%+ for most Spark queries, and deliver greater consistency.

Eliminate Ignite in-memory pauses, and process thousands of transactions per second in low milliseconds while scaling to petabytes of data.

Deliver tighter response-time SLAs in Hazelcast, including in small heaps where Hazelcast stores 500MB to 1.5GB data sizes.

Improve web server responsiveness and reduce pauses on less infrastructure.

Eliminate application jitter, response time inconsistency and in-memory data limitations, including JBoss Data Grid, EAP and middleware applications.

Improve consistency and reliability in memory-sensitive ZooKeeper-managed infrastructures, including Kafka event-streaming infrastructures.