Azul Recognizes Winners of its Inaugural 2024 Azul Java Hero Awards for Innovative, World-Class Java Deployments

Improve Apache Solr search performance while cutting costs across your stack

Beat SLAs while dramatically reducing costs. Impossible? Not with Azul.

The Azul Platform optimizes Apache Solr to drive SLA-beating, infrastructure costs-saving, Java-based search experiences for websites, e-Commerce platforms, records (e.g., healthcare), content management systems, and more. Solr rarely operates standalone, often alongside Spark, Kafka, and Cassandra. Deploy Azul across all your big data technologies and applications.

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Reduce infrastructure overhead.

Customers running Solr on the cloud report nearly 40% fewer cloud instances needed with Azul Platform Prime, and significantly improved memory utilization on existing resources.

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Increase throughput.

Increase data densities by 20%, in some cases significantly greater.

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Run Solr faster.

Run Solr 30% faster compared to OpenJDK HotSpot.

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“Without Azul Prime, we would not have been able to deploy Apache Solr for our production system. Our customers could have experienced long pauses when searching for critical documents.”

Mou Nandi, Search Engineer and Architect
Solr Throughput by Query on Azul Platform Prime vs OpenJDK

Solr: 30% Faster with Azul Prime

We compare Solr throughput on Azul Zulu Prime with Solr throughput on “unimproved” OpenJDK. Results: 29% to 37% faster with Azul Prime.

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Supercharge Solr.

Learn how the Azul Platform supercharges your Solr search capabilities and lowers your costs, on prem and in the cloud.

Read the White Paper
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Using Elasticsearch?

Performance improvements, reduced stop-the-world pauses, and significant cost savings are there to be had using Platform Prime with Elasticsearch.

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Improve performance and reduce costs.

Drive better Java performance with less infrastructure and less troubleshooting time, by far, than you’re currently investing.

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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.