Qdrant Hybrid Cloud

A premium vector database capability within the DataRobot Generative AI platform that stores chunked unstructured text and their embeddings for retrieval-augmented generation (RAG). Users can create vector database objects, connect supported data sources from the DataRobot Data Registry, configure embeddings and chunking, and attach these vector databases to LLM blueprints in the playground to ground model responses in proprietary data.

DataStax Astra DB is a managed, serverless vector database built on Apache Cassandra with integrated JVector for AI vector storage and search. It offers serverless scaling, global distribution, hybrid search capabilities, and seamless integrations with LangChain and LlamaIndex. Ideal for enterprise RAG pipelines and real-time AI applications, it provides multi-region replication and zero-ops management superior to self-hosted Milvus.

State-of-the-art foundational model for ranking with 4096 context length and multilingual support for 100+ languages. Offers exceptional performance on BEIR benchmarks and specialized domains including finance, e-commerce, and enterprise search.

Built into the Salesforce platform, Data Cloud Vector Database ingests various large datasets from customer interactions, classifies and organizes unstructured data, and merges it with structured data to enrich customer profiles and store as metadata in Data Cloud. It enhances generative AI by providing more relevant, accurate, and up-to-date responses through improved data retrieval and semantic search capabilities.

Instaclustr offers comprehensive managed services for vector databases, handling deployment, configuration, ongoing maintenance, tuning, optimization, scalability, security, and data protection. This allows organizations to offload the complexities of managing their vector database infrastructure and focus on their core business objectives.

Open-source federated search platform for privacy-preserving vector similarity search across distributed enterprise data sources without data migration or central storage, unlike centralized vector DBs like Pinecone that require uploading all data to a single service. Enables multi-node federation querying 100+ heterogeneous sources simultaneously, using LLM embeddings for re-ranking unified results while keeping data local for enhanced privacy and compliance. Ideal for federated learning scenarios and data-sovereign AI applications.