Blogs
Developer insights and practical how-to articles from our experts to inspire and empower your search experience.
Adding document level security (DLS) to your internal knowledge search
Learn how to secure your internal knowledge lake and offer personalized search for your end-users using document level security (DLS).
What happened in Lucene land in 2023?
2023 has been another big year for Apache Lucene, this blog reviews major milestones of 2023
How to ingest data from Snowflake to Elasticsearch
Learn how to ingest data from Snowflake to Elasticsearch using Logstash or a Snowflake Elasticsearch Python Script.
AI plagiarism: Plagiarism detection with Elasticsearch
Here's how to check for AI plagiarism using Elasticsearch, focusing on use cases with NLP models and Vector Search.
Introducing kNN Query: An expert way to do kNN search
Explore how the kNN query in Elasticsearch can be used and how it differs from top-level kNN search, including examples.
Apache Lucene 9.9, the fastest Lucene release ever
Lucene 9.9 brings major speedups to query evaluation. Here are the performance improvements observed in nightly benchmarks & optimization resources.
MAXSCORE & block-max MAXSCORE: More skipping with block-max MAXSCORE
Learn about MAXSCORE, block-max MAXSCORE & WAND. Improve the MAXSCORE algorithm to evaluate disjunctive queries more like a conjunctive query.
RAG evaluation metrics: A journey through metrics
Explore RAG evaluation metrics like BLEU score, ROUGE score, PPL, BARTScore, and more. Discover how Elastic is evaluating RAG with UniEval.
Retrieval Augmented Generation (RAG) using Cohere Command model through Amazon Bedrock and domain data in Elasticsearch
Learn how to implement Retrieval Augmented Generation (RAG) using Cohere Command model via Amazon Bedrock & domain data in Elasticsearch.
Domain specific generative AI: pre-training, fine-tuning, and RAG
Explore strategies for integrating domain-specific knowledge into large language models (LLMs) through pre-training, fine-tuning, and RAG.
Understanding fused multiply-add (FMA) within vector similarity computations in Lucene
Learn how to use fused multiply-add (FMA) within vector similarity computations in Lucene and discover how FMA can improve performance.
