The DataRobot vector databases feature provides FAISS-based internal vector databases and connections to external vector databases such as Pinecone, Elasticsearch, and Milvus. It supports creating and configuring vector databases, adding internal and external data sources, versioning internal and connected databases, and registering and deploying vector databases within the DataRobot AI platform to power retrieval-augmented generation and other AI use cases.
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A managed service and tooling offering from Instaclustr that helps teams operate and optimize vector databases for GenAI and Retrieval-Augmented Generation (RAG) workloads, providing expertise and infrastructure management for production deployments.
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.
A critical emerging technology focused on processing, storing, and retrieving vast amounts of high-dimensional vector data rapidly and efficiently. Unlike traditional databases, they offer unique advantages for use cases such as image and video recognition, natural language processing (NLP), and Retrieval-Augmented Generation (RAG).
Pinecone is a fully managed vector database designed for high‑performance semantic search and AI applications. It provides scalable, low-latency storage and retrieval of vector embeddings, allowing developers to build semantic search, recommendation, and RAG (Retrieval-Augmented Generation) systems without managing infrastructure.
Google Cloud's fully managed, PostgreSQL-compatible database service that offers vector capabilities, leveraging the power of PostgreSQL and pgvector for AI applications.
Microsoft Azure's managed service for PostgreSQL, which supports the pgvector extension, enabling robust vector database capabilities in the cloud for AI and machine learning workloads.
name: DataRobot Vector Databases slug: datarobot-vector-databases url: https://docs.datarobot.com/en/docs/api/reference/sdk/CHANGES.html vendor: DataRobot category: managed-vector-databases featured: true images:
DataRobot Vector Databases provide FAISS-based internal vector stores and managed connections to external vector databases. They are integrated into the DataRobot AI platform to support retrieval-augmented generation (RAG) and other embedding-based AI workloads.
The feature focuses on creating and configuring vector databases, managing versions, and registering and deploying these databases as part of production AI systems.
Pricing information is not provided in the available content. Refer to DataRobot’s official pricing or sales materials for details on plans and costs related to vector databases.