Managed Vector Search
Pinecone is a fully managed vector database that makes it easy to add vector search to production applications. It combines vector search libraries, capabilities such as filtering, and distributed infrastructure to provide high performance and reliability at any scale.
Add vector search to production applications in less time than it takes to train a model.
Go to production with a few lines of code, without breaking a sweat or slowing down
- Deploy and start using the service with a few lines of code. The REST API, clients (Python, Java, Go), and web console make it easy and quick to integrate into production applications.
- Approximate Nearest Neighbor (ANN) search with filtering, live index updates, namespacing, string IDs, batch queries, vector fetch operations, and more.
Scale and Performance
Search through billions of vectors in tens of milliseconds.
- Automatic scaling with data shards and replicas, eventual consistency, and data persistence on distributed infrastructure.
- Sub-100ms query latency and high recall rates at scale, even with billions of vectors and tens of thousands of queries per second.
- Maximum throughput (QPS) increases linearly with added replicas, without limits.
- Hybrid in-memory/on-disk storage is up to 10x more cost-effective for large data volumes compared to in-memory databases.
We obsess over operations and security so you don't have to.
- Just create an account and we'll manage the infrastructure with high availability, geo-replication, and 24/7 operational support.
- Pinecone runs on secure AWS or GCP environments in multiple regions, with dedicated deployments available. Your data is secured in isolated containers and encrypted in transit.
Designed for speed,
Designed for speed,
scale, and ease of use.
One of the world's largest social media platforms increased user enagement with Pinecone
Content recommendation engine powered by Pinecone vector search.
queries per second
search latency (p99)