KiviDB

KiviDB is a Redis-compatible in-memory database with vector search for AI and real-time apps.

KiviDB is a Redis-compatible in-memory database that includes vector search capabilities designed specifically for artificial intelligence and real-time applications. It is built to use every available CPU core to deliver fast performance as an in-memory cache and vector database. Users can deploy the software independently via self-hosting or choose the managed KiviDB Cloud option. It caters to developers and organizations building high-performance real-time systems and AI workloads. The platform combines traditional caching functions with advanced vector search in a single system.

KiviDB at a glance

Best for: Software engineer
Runs on: self-hosted
Pricing: Freemium
Released: May 2026
Category: AI search engine
Website: kividb.io

Key features

Redis-compatible interface
In-memory data storage
Vector search capabilities
Multi-core processor utilization
Self-hosting option
Cloud hosting option

Use it for

Caching data for real-time applications
Running vector search for AI workloads
Deploying a high-speed in-memory database

Alternatives to KiviDB

zvec — It is a pure local, serverless vector database providing fast hybrid search.
Memvid — Single-file architecture replaces complex RAG pipelines with portable storage.
Milvus — Distributed vector search that scales to billions of vectors
Searchbase — Independent web access with support for REST, MCP, self-hosting, and managed cloud.
SereneDB — Executes search and analytics queries with a PostgreSQL-compatible frontend.
RuVector — Provides persistent vector retrieval, graph relationships, and local decision making in Rust.
Vespa — Combines vector database capabilities with distributed machine-learned model inference.
Open Glean — Provides agents with structured state and relationship-based context rather than just similarity.
XERJ — It answers agent questions from an index instead of wasting tokens on context windows.
Exa — Provides high-accuracy web search and deep research endpoints for AI agents.
txtai — Combines vector indexes, graph networks, and relational databases in one framework.
SeekStorm — It delivers sub-millisecond lexical and vector search performance in Rust.

All KiviDB alternatives