Vector Databases

A vector database is a specialized DBMS that stores vector embeddings utilizing innovative techniques for storage, indexing, and query processing. They offer data management capabilities, such as CRUD and language bindings to widely used data science languages such as Python, SQL, Java, and Tensorflow. Additionally, they deliver advanced features such as high-speed ingestion, sharding, and replication.

Vector databases are designed to handle critical query and algorithmic styles seen in similarity search, anomaly search, observability, fraud detection, and IoT sensor analytics. Such emerging styles are the outcome of digital transformation and the rise of generative AI.

A Comprehensive Guide to Vector Databases - KDB.AI

A Fun & Absurd Introduction to Vector Databases • Alexander Chatzizacharias • GOTO 2024 - YouTube

Databases

• pinecone
• LanceDB
• Epsilla
• Welcome | Weaviate - Vector Database
• PostgresML: Leveraging Postgres as a Vector Database for AI
• Learn Vector Database in 10 Mins - Hottest AI Apps DB!
• What Are Vector Databases? | MongoDB
• Chroma - the AI-native open-source embedding database
  • GitHub - chroma-core/chroma: the AI-native open-source embedding database
  • Chroma Vector Database: Retrieval for LLMs (Hammad Bashir + Liquan Pei)
• GitHub - milvus-io/milvus: A cloud-native vector database, storage for next generation AI applications
  • Vector database - Milvus

Links

• The 5 Best Vector Databases | A List With Examples | DataCamp
• Key considerations when choosing a database for your generative AI applications | AWS Database Blog
• InterviewReady | System Design Course | Gaurav Sen