Check out the blogs that falls under the category Vector Search. Learn more about the vector search best practices – interacting with AI LLMs and more
Category: Vector Search

New Couchbase Capella Advancements Fuel Development
Today we are pleased to announce three major advancements for Capella, the cloud database platform for modern applications, including GenAI, vector search, and mobile application services. First, the general availability of Capella Columnar, which enables real-time, zero ETL JSON-native data...

Vector Search at the Edge with Couchbase Mobile
We’re pleased to announce the release of Couchbase Lite 3.2 with support for vector search. This launch follows the coattails of vector search support on Capella and Couchbase Server 7.6. Now, with vector search support in Couchbase Lite, we enable...

Build Performant RAG Applications Using Couchbase Vector Search and Amazon Bedrock
Generative AI (GenAI) has the potential to automate work activities that currently occupy 60 to 70 percent of employees’ time, leading to substantial productivity gains across various industries. However, a General Purpose (GP) LLM’s knowledge is confined to its training...

Build Faster and Cheaper LLM Apps With Couchbase and LangChain
New Standard, Semantic and Conversational Cache With LangChain Integration In the rapidly evolving landscape of AI application development, integrating large language models (LLMs) with enterprise data sources has become a critical focus. The ability to harness the power of LLMs...

Get Started With Couchbase Vector Search In 5 Minutes
What is a Vector A Vector is an object that represents a real-world item as an array of floating numbers. Each item in the real world is represented in Vector format(as an array) and has many dimensions (attributes) associated with...

Accelerate Couchbase-Powered RAG AI Application With NVIDIA NIM/NeMo and LangChain
Today, we’re excited to announce our new integration with NVIDIA NIM/NeMo. In this blog post, we present a solution concept of an interactive chatbot based on a Retrieval Augmented Generation (RAG) architecture with Couchbase Capella as a Vector database. The retrieval...

Enhancing GenAI for Privacy and Performance: The Future of Personalized AI with Edge Vector Databases
The evolution of Generative AI (GenAI) is marked by a significant transition from model development to application development. As these AI models mature, the focus shifts to integrating them into real-world applications, bringing about new challenges. Application developers and infrastructure...

Develop Performant RAG Apps With Couchbase and Vectorize
For technology leaders and developers, the process of integrating rich, proprietary data into generative AI applications is often filled with challenges. Vector similarity search and retrieval augmented generation are powerful tools to help with this, but one mistake extracting, chunking,...

How Adaptive Applications Unlock Innovation in a New AI Age
We stand on the verge of a generative AI (GenAI) revolution. Some 98% of organizations have specific GenAI goals for 2024 — accounting for nearly a third of digital modernization spend last year and in 2024, according to new research...

Couchbase Capella™ Wins Two Awards in the 2024 Stevie American Business Awards
As the cloud database market continues to evolve, Couchbase is committed to providing unmatched versatility, performance, and scalability to empower customers and partners to be at the forefront of innovation. As a testament to Couchbase’s continued advancements, we’re thrilled to...

Querying Vectors And Things That Can Go Wrong With Them
Couchbase 7.6 introduces Vector Search into the Couchbase architecture, expanding its search capabilities by leaps and bounds. This article showcases how this affects search queries, how we have to adapt in certain situations and how to efficiently use this latest...