Category: Java

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Jingra: A Reproducible Framework for Vector Search Benchmarking

Jingra is an open source benchmarking framework that runs the same vector search workload across Elasticsearch, OpenSearch and Qdrant so you can compare engines under identical, reproducible conditions.

Sachin Frayne

New Elasticsearch ES|QL plugin for IntelliJ IDEA

Build and run Elasticsearch ES|QL queries in your IDE with the new plugin for IntelliJ IDEA.

Laura Trotta

Testing Elasticsearch. It just got simpler.

Explaining how Elasticsearch integration tests have become simpler thanks to improvements in Elasticsearch 9.x, the modern Java client, and Testcontainers 2.x.

Piotr Przybyl

Hybrid search with Java: LangChain4j Elasticsearch integration

Learn how to use hybrid search in LangChain4j via its Elasticsearch integrations, with a complete Java example.

Laura Trotta

LangChain4j with Elasticsearch as the embedding store

LangChain4j (LangChain for Java) has Elasticsearch as an embedding store. Discover how to use it to build your RAG application in plain Java.

David Pilato

Testing your Java code with mocks and real Elasticsearch

Learn how to write your automated tests for Elasticsearch, using mocks and Testcontainers

Piotr Przybyl

Introducing LangChain4j to simplify LLM integration into Java applications

LangChain4j (LangChain for Java) is a powerful toolset to build your RAG application in plain Java.

David Pilato

ES|QL queries to Java objects

Learn how to perform ES|QL queries with the Java client. Follow this guide for step-by-step instructions, including examples.

Laura Trotta

Ready to build state of the art search experiences?

Sufficiently advanced search isn’t achieved with the efforts of one. Elasticsearch is powered by data scientists, ML ops, engineers, and many more who are just as passionate about search as you are. Let’s connect and work together to build the magical search experience that will get you the results you want.

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