Category: Vector Database

Articles tagged Vector Database

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Better Binary Quantization (BBQ) vs. Product Quantization
Elasticsearch Labs

Better Binary Quantization (BBQ) vs. Product Quantization

Why we chose to spend time working on Better Binary Quantization (BBQ) instead of product quantization in Lucene and Elasticsearch.

Benjamin Trent
Federated SharePoint searches with Azure OpenAI Service On your data
Elasticsearch Labs

Federated SharePoint searches with Azure OpenAI Service On your data

Using Azure OpenAI Service on your data with Elastic as vector database.

Gustavo Llermaly
How to use hybrid search for an e-commerce product catalog
Elasticsearch Labs

How to use hybrid search for an e-commerce product catalog

Learn how to use hybrid search to build an e-commerce product catalog, using faceting, promotions, personalization and behavioral analytics.

Andre Luiz
Better Binary Quantization (BBQ) in Lucene and Elasticsearch
Elasticsearch Labs

Better Binary Quantization (BBQ) in Lucene and Elasticsearch

How Better Binary Quantization (BBQ) works in Lucene and Elasticsearch.

Benjamin Trent
Hybrid search with multiple embeddings: A fun and furry search for cats!
Elasticsearch Labs

Hybrid search with multiple embeddings: A fun and furry search for cats!

A walkthrough of how to implement different types of search - lexical, vector and hybrid - on multiple embeddings (text and image). It uses a simple and playful search application on cats.

Jo Ann de Leon
RaBitQ binary quantization 101
Elasticsearch Labs

RaBitQ binary quantization 101

Understand the most critical components of RaBitQ binary quantization, how it works and its benefits. This guide also covers the math behind the quantization and examples.

John Wagster
Unlock the power of your data with RAG using Vertex AI and Elasticsearch
Elasticsearch Labs

Unlock the power of your data with RAG using Vertex AI and Elasticsearch

Unlock your data's potential with RAG using Vertex AI and Elasticsearch. This blog series covers data ingestion into Elasticsearch for a robust knowledge base for creating advanced RAG based search applications.

Juan Bustos
Building a search app with Blazor and Elasticsearch
Elasticsearch Labs

Building a search app with Blazor and Elasticsearch

Learn how to build a search application using Blazor and Elasticsearch, and how to use the Elasticsearch .NET client for hybrid search.

Gustavo Llermaly
LangChain4j with Elasticsearch as the embedding store
Elasticsearch Labs

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
Vertex AI integration with Elasticsearch open inference API brings reranking to your RAG applications
Elasticsearch Labs

Vertex AI integration with Elasticsearch open inference API brings reranking to your RAG applications

Google Cloud customers can use Vertex AI embeddings and reranking models with Elasticsearch and take advantage of Vertex AI’s fully-managed, unified AI development platform for building generative AI apps.

Tim Grein
Navigating an Elastic vector database
Elasticsearch Labs

Navigating an Elastic vector database

An overview of operating a modern Elastic vector database with practical code samples.

Justin Castilla
Elasticsearch open Inference API support for AlibabaCloud AI Search
Elasticsearch Labs

Elasticsearch open Inference API support for AlibabaCloud AI Search

Discover how to use Elasticsearch vector database with AlibabaCloud AI Search, which offers inference, reranking, and embedding capabilities.

Dave Kyle