Best Neon Alternatives & Competitors

Milvus is an open-source vector database built for scalable similarity search, capable of handling billions of vectors. Backed by the Zilliz company, Milvus supports multiple index types (IVF, HNSW, DiskANN), GPU-accelerated search, and multi-tenancy. Zilliz Cloud offers a fully managed version with automatic scaling. Milvus is widely used in enterprise deployments requiring high-throughput vector search at scale.

Pinecone is the most widely used managed vector database, purpose-built for similarity search and retrieval-augmented generation (RAG). It offers serverless and pod-based architectures, supporting billions of vectors with single-digit millisecond query latency. Pinecone provides metadata filtering, namespaces, and hybrid search combining dense and sparse vectors. Its managed service eliminates infrastructure complexity, making it the go-to choice for teams building semantic search, recommendation engines, and RAG-powered AI applications.

Qdrant is a high-performance open-source vector database written in Rust, optimized for speed and reliability. It supports advanced filtering with payload indexes, quantization for memory efficiency, and distributed deployments for horizontal scaling. Qdrant offers a managed cloud service and is popular with teams that need production-grade vector search with fine-grained control over indexing and query parameters.

Chroma is an open-source embedding database designed for simplicity and developer experience. It provides a lightweight, easy-to-use API for storing, querying, and filtering embeddings locally or in the cloud. Chroma is the default vector store in many LLM frameworks like LangChain and LlamaIndex, making it extremely popular for prototyping and building RAG applications quickly.

The #1 platform for pgvector. Open-source Firebase alternative with built-in vector search via Postgres.

Weaviate is an open-source vector database that combines vector search with structured filtering and generative capabilities. It supports multiple vectorization modules, hybrid search (combining BM25 and vector search), and built-in integrations with LLMs for retrieval-augmented generation. Weaviate offers both self-hosted and managed cloud deployments, with a GraphQL API that makes it easy to query complex data structures.

Neo4j is the world's leading graph database, widely used for building knowledge graphs that power AI applications. Its native graph storage and Cypher query language enable complex relationship queries, pattern matching, and path finding. Neo4j's GenAI integrations include vector search, LLM-powered knowledge graph construction, and GraphRAG capabilities that combine structured graph data with LLM reasoning for more accurate, explainable AI.

MongoDB Atlas Vector Search adds vector similarity search directly into MongoDB, allowing developers to combine vector embeddings with traditional document queries, full-text search, and geospatial queries in a single database. It eliminates the need for a separate vector database for teams already using MongoDB.

Elasticsearch has added k-NN vector search capabilities to its distributed search and analytics engine. Teams can combine vector similarity search with Elasticsearch's powerful full-text search, filtering, and aggregation features in a single platform, making it ideal for hybrid search applications at enterprise scale.

Redis provides vector similarity search as part of its in-memory data platform. Redis Vector Search enables real-time semantic search with sub-millisecond latency, supporting HNSW and FLAT indexing algorithms. Ideal for applications requiring both traditional caching and vector search in a single data layer.

High-performance analytical database with vector search. Standard for observability + embeddings.

TigerGraph is a scalable graph database platform for advanced analytics and AI.

Vespa is an open-source search and recommendation engine combining vector search, full-text search, and structured queries.

LanceDB is an embedded, serverless vector database that runs inside your application process with zero infrastructure. Built on the Lance columnar format, it supports multimodal data (text, images, video), automatic versioning, and scales from local development to cloud deployments.

Turbopuffer is a serverless vector database designed for speed and cost efficiency.

SingleStore is a distributed SQL database with built-in vector search capabilities.

ArangoDB is a multi-model database supporting graph, document, and search in a single engine.