Indexing and Vector Database
What is a vector database? | Google Cloud
A vector database is any database that allows you to store, index, and query vector embeddings, or numerical representations of unstructured data.
Concept of Index in VectorDB - API - OpenAI Developer Forum
Sometimes people just use the word “Index” as a general term for what it is that vector embedding (i.e. RAG approach) is doing. I wouldn't get ...
Mastering RAG: Choosing the Perfect Vector Database - Galileo
To achieve fast query speed, vector databases employ various optimization techniques. These may include index structures, caching mechanisms, ...
How to Index Fields for Vector Search - MongoDB Atlas
Use the Atlas Vector Search type to index vector embeddings for vector search using the vectorSearch type.
Vector Databases: Intro, Use Cases, Top 5 Vector DBs - V7 Labs
Vector databases have had a huge impact on AI products involving Large Language Models and semantic search. Let's see if they're the right ...
An Introduction to Vector Databases for Beginners | Xomnia
Vector indexing is the process of organizing vector embeddings in a structured manner to expedite retrieval operations. Techniques such as ...
Vectors are lists of numbers representing a measurement in multidimensional space. There are many types of vectors, e.g. embeddings used for semantic search, ...
What is a Vector Database? - TechTarget
Vector search. When a user or application submits a database query for a similarity search, it's converted into a vector representation. In many cases, an ...
What is a vector database? - Ubuntu
These databases are designed to store, index, and query vector embeddings or numerical representations of unstructured data, including text ...
Using OpenSearch as a Vector Database
OpenSearch provides an integrated vector database that can support AI systems by serving as a knowledge base. This benefits AI applications like generative AI ...
Vector Database : A Beginner's Guide - EightGen AI Services
Brute-Force Indexing: This technique involves storing all vectors in a database and performing a linear scan to find the nearest neighbors for a ...
A gentle introduction to vector databases | Hacker News
The way that vector indices work typically can make doing CRUD with them a real challenge. There is definitely novelty in being able to do both ...
Do you need a specialized vector database to implement vector ...
Now, in addition to the standard unstructured data, you can create an index definition on top of your collection that says where the vector ...
[D] Is creating indexes and using vector databases really required in ...
If you have one single 3 paged document then yeah you don't need RAG, you can just pass the whole document. But if instead you need to determine ...
Redis includes a high-performance vector database that lets you perform semantic searches over vector embeddings.
Navigating Vector Databases: Indexing Strategies, GPU, and More
On this episode of the ML Platform Podcast, Frank Liu discusses the basics, problems and challenges of vector databases, including indexing ...
Create a Vector Search Index Configuration with Advanced Setup
Required Editions and User Permissions · From App Launcher, select Data Cloud. · Click Search Index > New. · Click Advanced Setup > Next. · On the Select Source ...
5 Steps to Implement a Vector Database Successfully - RisingWave
Another critical component of vector databases is the indexing mechanism. This structure organizes vectors spatially for quick retrieval based on similarity ...
A Beginner-friendly and Comprehensive Deep Dive on Vector ...
Indexing the database provides a quick lookup mechanism, especially in cases where near real-time latency is paramount. More specifically, when ...
Using Vector Databases to Extend LLM Capabilities - .NET
Vector search works by analyzing the vector representations of your data that you created using an AI embedding model such the Azure OpenAI ...