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The Best JVM for Big Data - Zing

Gain maximum value from your Big Data initiatives by
deploying a better JVM

Big Data without limits

"Big data and large graphs are a sweet spot for Neo4j. Azul's proven technology for JVM performance makes Zing a great match for Neo4j, which leverages in-memory processing. Azul will help our largest customers push past the limits of today's JVM technology."
- Philip Rathle, Senior director of products, Neo Technology

Essential Technology for Big Data success - Zing

Designed for applications that are critical to business results, Zing is the only JVM that supports highly consistent and pauseless execution for HBase and HDFS. Zing lowers average latency up to 70% without coding changes and makes larger in-memory indexes practical. Plus, for Big Data driven applications where revenue is directly dependent on response times, Zing can increase success rates (3 – 4X for one recent customer) and total end-user engagements

Feedzai Case Study

Big Data Partners

Azul’s Big Data partners include Datastax, Cloudera, Feedzai, Neo Technologies, and Red Hat

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Support massive in-memory datasets

Zing supports up to 8 TB of memory in a single JVM instance

Hadoop, Cassandra, Elastic, Lucene, Solr, Spark and more

With Zing, you’ll always deliver predictable performance

Ideal for real-time risk

Zing makes real-time analytics using Big Data feasible. And practical

Enterprise search? No problem

Zing is the best JVM for Elastic, Lucene and Solr

Resources Section

Apache Cassandra

Get the benchmark

JBoss Data Grid

Get the White Paper

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Java is key to most Big Data technologies, and Zing provides key advantages for Big Data deployments. Now you can deliver predictable performance for your most demanding Big Data workloads.

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