Pinecone vs Vespa

Pinecone vs. Vespa

Compare Pinecone vs. Vespa by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.

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Pinecone vs. Vespa on Scalability

PineconeVespa

Separation of storage and compute

Yes, for the Serverless tier.

❌

Separation of query and insertions

Yes, for the Serverless tier.

Yes.

Multi-replication

❌

Dynamic segment placement vs. static data sharding

Static sharding

Both

Cloud-native

❌

Billion-scale vector support

❌

Pinecone

Pinecone supports the separation of compute and storage with their Serveless Tier.

For its POD-based clusters, Pinecone employs static sharding, which requires users to manually reshard data when scaling out the cluster.

Vespa

Vespa is a scalable search engine with a robust distributed architecture that supports horizontal scaling by adding more nodes. It features automatic sharding and data redistribution, allowing it to efficiently manage large datasets and high query volumes.

Pinecone vs. Vespa on Functionality

PineconeVespa

Role-based Access Control (RBAC)

Yes, with limited roles (only Org Owner & members are supported)

❌

Disk Index support

Available with the Pinecone S1 solution only

Yes (paged tensor attributes)

Hybrid Search (ie Scalar filtering)

Yes. Sparse & Dense Vectors and Scalar filtering.

Yes, vector search & keyword seach

Partitions/namespaces/logical groups

Yes. Users cans organizes data into namespaces and should aware that there are a limited number of namespaces available. Please consult with Pinecone on the limitations.

❌

Index type supported

Closed source Index (proprietary)

HNSW, Hybrid HNSW-IF (Inverted File), paged tensor attributes

Multiple in-memory indexes support

❌

Pinecone

RBAC is not enough for large organizations. Storage optimized (S1 ) has some performance challenges and can only get 10-50 QPS. The number of namespaces is limited and users should be careful when using metadata filtering as a way around this limitation as it will have a big impact on performance. Furthermore, data isolation is not available with this approach.

Vespa

Vespa is a powerful search engine and vector database that can handle multiple searches simultaneously. It's great at vector search, text search, and searching through structured data.

Pinecone vs. Vespa on Purpose-built

PineconeVespa

Purpose-built for Vectors

❌

Yes.

Tunable consistency

❌

Support for both stream and batch of vector data

❌

Binary Vector support

❌

Multi-language SDK

REST API, Python, Node.js

Python, Java

Database rollback

yes, with the collection backup & restore

❌

Pinecone vs. Vespa: what’s right for me?

Pinecone

Pinecone is a managed, cloud-native vector database.

SaaS

Vespa

Vespa is a powerful search engine and vector database that can handle multiple searches simultaneously. It's great at vector search, text search, and searching through structured data.

Apache 2.0