Managed vector database platform for semantic search and retrieval augmented generation (RAG) in AI applications.
Turnpike platform for LLM-powered search and RAG with built-in vector indexing.
Usage-based pricing.
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Haystack
Haystack is a Python library for building vector search and embedding-based retrieval pipelines, integrating ANN indexes without requiring full databases. Key features include support for HNSW, FAISS indexes, quantization options, and multi-language embeddings. Perfect for prototyping RAG systems and embedded AI apps; more flexible than hnswlib, lighter than Milvus for development workflows.
DataRobot Vector Database
DataRobot Vector Database is a managed vector store capability within the DataRobot AI Platform that allows users to create, register, deploy, and update vector databases for AI workloads, including RAG and semantic search. It integrates with NVIDIA NIM embeddings and supports both built-in and bring-your-own embeddings for building production-grade vector search solutions.
Implement two-tower retrieval for large-scale candidate generation
A Google Cloud reference architecture demonstrating an end-to-end two-tower retrieval system for large-scale candidate generation that uses Vertex AI and vector similarity search concepts to learn and serve semantic similarity between entities.
Algolia
Search platform with vector search capabilities for fast and relevant AI-powered recommendations and discovery.
Cloudflare Vectorize
Edge-native managed vector database integrated with Cloudflare Workers. Supports 50,000 namespaces and up to 5M vectors per index for low-latency applications.
DataStax Astra
Managed database built on Cassandra with vector search capabilities, excelling in real-time updates and immediate consistency. Ideal for operational workloads requiring high throughput.
