Category: Vector Database
Articles tagged Vector Database
Looking back: Elastic's vector search improvements in Elasticsearch & Lucene
Looking back at Elastic's vector search innovations in Elasticsearch and Lucene.
Vector embeddings made simple with the Elasticsearch-DSL client for Python
Learn how to ingest and search dense vectors in Python using the Elasticsearch-DSL client.
Advanced RAG techniques part 2: Querying and testing
Discussing and implementing techniques which may increase RAG performance. Part 2 of 2, focusing on querying and testing an advanced RAG pipeline.
Advanced RAG techniques part 1: Data processing
Discussing and implementing techniques which may increase RAG performance. Part 1 of 2, focusing on the data processing and ingestion component of an advanced RAG pipeline.
Phi-3 small models, Elastic & RAG: Creating a smart ordering system
Deploying Phi-3 models on Azure AI Studio and using them with Elastic Open Inference Service to create a RAG application.
Building multilingual RAG with Elastic and Mistral
Building a multilingual RAG application using Elastic and Mixtral 8x22B model
Mistral AI embedding models now available via Elasticsearch Open Inference API
Learn more about how to use Mistral embeddings with Elastic built search experiences!
The sparse vector query: Searching sparse vectors with inference or precomputed query vectors
Learn about the Elasticsearch sparse vector query, how it works, and how to effectively use it.
Bit vectors in Elasticsearch
Discover what are bit vectors, their practical implications and how to use them in Elasticsearch.
Build a RAG application with Elasticsearch's semantic_text and Amazon Bedrock
Learn how to build a RAG application using Elasticsearch's semantic_text mapping type and Amazon Bedrock without leaving Elastic.
Elasticsearch open inference API adds Amazon Bedrock support
Elasticsearch open inference API added Amazon Bedrock support. Here's how to use Amazon Bedrock models via Elasticsearch's open inference API.
