Comparisons
OpenSearch vs KDB.AI

OpenSearch vs. KDB.AI

Compare OpenSearch vs. KDB.AI 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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OpenSearch vs. KDB.AI on Scalability

OpenSearchKDB.AI

Separation of storage and compute

❌

Separation of query and insertions

Yes.

Multi-replication

❌

Dynamic segment placement vs. static data sharding

Both

Neither.

Cloud-native

❌

Billion-scale vector support

❌

OpenSearch

OpenSearch supports horizontal scaling, cluster management optimizations, and efficient shard allocation, making it suitable for handling large datasets and high query loads effectively.

KDB.AI

KDB.AI is a scalable vector database.

OpenSearch vs. KDB.AI on Functionality

OpenSearchKDB.AI

Role-based Access Control (RBAC)

❌

Disk Index support

❌

Yes (qFlat and qHNSW)

Hybrid Search (ie Scalar filtering)

yes, vector search & keyword search & scalar filtered search

Yes. Hybrid Sparse & Dense Search

Partitions/namespaces/logical groups

❌

Index type supported

ANN

Flat, qFlat, IVF, IVFPQ, HNSW, and qHNSW.

Multiple in-memory indexes support

❌

OpenSearch

OpenSearch supports:

Vectors with up to 16,000 dimensions.
Vector generation through external libraries or directly within OpenSearch.
Both binary and dense vectors.
Cosine Similarity, Inner Product, and L2 Distance (Euclidean).
Integration with multiple engines, including NMSLIB, Faiss, and Lucene, to facilitate vector indexing and searching.

KDB.AI

Built by KX, a database provider known for time-series data management, KDB.AI enables developers to bring temporal and semantic context and relevancy to their applications. It supports various search types, including vector similarity search, hybrid sparse and vector search, and Non-Transformed TSS, a similarity search algorithm specific for time series data. It uses Cosine Similarity, Inner Product, and L2 Distance (Euclidean) for similarity metrics.

OpenSearch vs. KDB.AI on Purpose-built

OpenSearchKDB.AI

Purpose-built for Vectors

No. Vector search is an add-on to OpenSearch.

Yes.

Tunable consistency

❌

Support for both stream and batch of vector data

❌

Binary Vector support

❌

Multi-language SDK

Java, Python, JavaScript, Go, and .Net

Python

Database rollback

❌

OpenSearch vs. KDB.AI: what’s right for me?

OpenSearch

OpenSearch is an open-source software suite for search, analytics, security monitoring, and observability applications. It is not purpose-built for vector storage and search workloads but introduces a vector search plugin to provide this capability. Amazon OpenSearch Service is an AWS-managed service for OpenSearch.

Apache 2.0

KDB.AI

KDB.AI is a powerful knowledge-based vector database and search engine that allows you to build scalable, reliable AI applications using real-time data.

Proprietary license