ElasticSearch
Lucene based search server.
Lucene based search server.
Reviews for ElasticSearch
Hear what real users highlight about this tool.
Reviewers highlight ElasticSearch for speed, flexibility, and broad integration. Maker feedback stands out: makers of Playbook say it reliably powers their search; makers of Gan.AI praise its analytics and logs for debugging; makers of fn7 Helix value having vector and traditional search in one system. Other makers note strong scalability, hybrid/vector support, and dependable community backing. Users find it easy to use with wide features and helpful for search, though general comments are brief. Overall sentiment is strongly positive.
This AI-generated snapshot distills top reviewer sentiments.
OnSpace relies on Elasticsearch's powerful search engine to deliver fast, scalable search and real-time analytics for high-performance applications.
Still the best all-purpose search engine when speed, flexibility, and integration matter. We use it heavily for vector + hybrid search. Scales better than most, works great with embeddings.
Nothing beats the speed and reliability of an elasticsearch server. ETL with sublime caching ensures our users get a premium experience
ElasticSearch powers AltMarket’s search, giving users fast, fuzzy, and intuitive results. It turned product discovery into a smooth experience.
Elasticsearch – Powered our fast, scalable news search engine. With its Lucene-based indexing, we’re able to serve Millions of articles with lightning-fast performance, support multi-language queries, and enable smart filtering for bias, sentiment, and source comparison. It’s the backbone of our search experience on The Balanced News.
ElasticSearch enables us to deliver blazing-fast and relevant product search experiences. It’s powerful, flexible, and battle-tested at scale.
We chose ElasticSearch over alternatives like Algolia or basic database search because learning content requires contextual, semantic search capabilities that go beyond simple keyword matching. When users upload diverse materials - lecture PDFs, YouTube transcripts, handwritten notes - they need to find concepts across different content types using natural language queries. ElasticSearch's Lucene foundation gives us powerful text analysis, fuzzy matching for handwritten content recognition, and the ability to weight search results based on learning context. Unlike simpler search solutions, we can create custom analyzers that understand educational terminology and help users discover connections between concepts they studied weeks apart.
ElasticSearch stands out with its speed, scalability, and ecosystem maturity. It handles complex queries on massive datasets with ease, has powerful full-text search capabilities, and integrates seamlessly with tools like Kibana and Logstash — making it a go-to choice for real-time analytics and monitoring.
Detailed analytics and logs for error tracking and debugging
Elasticsearch powers real-time search and analytics at scale, making it perfect for Meet Pal’s AI infrastructure. It helps us provide fast and relevant responses to user queries by efficiently indexing and retrieving data. Its robust querying capabilities allow us to deliver personalized and timely recommendations with minimal latency.
If you already use ElasticSearch and don't want to spin up a new vector store, Pongo can be an easy way to add state of the art retrieval to your pipeline.