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YantrikDB System Properties

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Name

Description

YantrikDB is a store for AI-agent memory rather than a general-purpose DBMS. Alongside ordinary vector search it runs three background operations over stored records — temporal decay with a configurable half-life, consolidation of near-duplicate records into canonical ones, and detection of contradictions between records — and it maintains an entity graph over them. It ships in three forms from one engine: an embeddable library (no server process, like SQLite), a network server with an HTTP and binary API, and an MCP server that AI coding tools connect to directly.

Primary database model

Vector DBMS

Secondary database models

Document Stores
Graph DBMS
Key-value store

Website

yantrikdb.com

Technical documentation

github.com/yantrikos/yantrikdb (engine)
github.com/yantrikos/yantrikdb-server (server)
yantrikdb.com/guides

Developer

Pranab Sarkar (independent), India

Initial release

2026

Current release

engine 0.15.4, released 2026-08-18

License

Commercial or Open Source

Apache-2.0

Cloud-based only

Only available as a cloud service

no — self-hosted or embedded

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust (Python bindings; Python client SDK)

Server operating systems

Linux, macOS, Windows; Docker and Kubernetes manifests

Data scheme

schema-free records with typed metadata

Secondary indexes

yes — HNSW approximate-nearest-neighbour vector index

SQL

Support of SQL

APIs and other access methods

embedded Rust API, Python API, HTTP/REST, a binary wire protocol, and a Model Context Protocol (MCP) server

Supported programming languages

Rust, Python (any language over HTTP)

Partitioning methods

Methods for storing different data on different nodes

none (single node) — horizontal scaling is by namespace

Replication methods

Methods for redundantly storing data on multiple nodes

Raft-based cluster (openraft), 2 voters + 1 witness

Consistency concepts

Methods to ensure consistency in a distributed system

strong within a Raft cluster; single-node deployments are backed by SQLite

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID, via the SQLite storage layer

Durability

Support for making data persistent

yes (SQLite WAL)

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

no — persistent by default

User concepts

Access control

bearer-token access with per-tenant quotas in server mode; none in embedded mode. AES-256-GCM encryption at rest.

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