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.
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.
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.
Hybrid search with Java: LangChain4j Elasticsearch integration
Learn how to use hybrid search in LangChain4j via its Elasticsearch integrations, with a complete Java example.
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.
Testing your Java code with mocks and real Elasticsearch
Learn how to write your automated tests for Elasticsearch, using mocks and Testcontainers
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.
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.