As AI agents begin to permeate workflows across industries, the way data systems are designed is being redefined. Tiger Data, the company that previously built the database layer for billions of IoT devices, has unveiled Agentic Postgres, a new kind of database built specifically for agents: autonomous programs that learn, adapt, and operate in parallel.
Traditional databases were designed for linear applications and human users. But agents behave differently: they branch, explore, and evolve simultaneously. Supporting this new mode of computing requires databases capable of spawning infinite, safe copies of data, allowing agents to experiment, test, and learn continuously without compromising production systems or driving up costs.
“We defined the database for IoT. With Agentic Postgres, we are defining the database for agents: a new kind of user that requires infinite, reproducible environments to branch, explore, and adapt,” said Ajay Kulkarni, Co-Founder and CEO of Tiger Data. “Tiger already powers Fortune 500 companies in IoT, Web3, and AI, proving its readiness for production at scale.”
A New Foundation for Agentic Workloads
Available now on Tiger, Tiger Data’s fully managed Postgres cloud, Agentic Postgres introduces a key breakthrough: forkable infrastructure. This capability allows developers and AI agents to create instant, copy-on-write branches of both databases and storage volumes, making it possible to run parallel experiments safely and affordably.
Forkable infrastructure combines two capabilities that unlock what Tiger Data calls “safe, instant parallelism” for agent workloads:
- Forkable Databases: Developers can spin up zero-copy branches of Postgres itself (including schema, tables, and rows) in seconds. This enables teams to test new logic, debug issues, or run simulations without risking production data.
- Forkable Volumes: Beyond databases, these forks extend to the entire environment, including storage, embeddings, indexes, and artifacts, so each forked environment is a complete, reproducible snapshot that agents can use as if it were production-ready.
Together, these innovations allow developers to create hundreds or even thousands of parallel environments, paying only for incremental changes rather than full replicas. The design aims to scale toward “effectively infinite parallelism,” aligning with the exponential growth in agent workloads expected in coming years.
Three Primitives for the Agentic Era
In addition to forkable infrastructure, Agentic Postgres introduces three new primitives inside Postgres: Interface, Search, and Memory.
- Interface: A control plane accessible through REST APIs, CLI, and Model Context Protocol (MCP) endpoints, available today.
- Search: Hybrid retrieval capabilities combining vector search (via pgvectorscale, available today) and BM25 keyword search (in public preview).
- Memory: Persistent context for agents (such as conversation history, preferences, and shared state) accessible through APIs and MCP endpoints (public preview).
Together, these capabilities establish the foundation for agent-native applications that can recall, reason, and evolve over time.
“Interface, search, and memory are the foundation. Forkable infrastructure is the breakthrough. Together, they make Tiger the Postgres database for agents,” the company noted in its announcement.
An Alternative to Fragmented Stacks and Lock-In
Today’s AI infrastructure landscape is riddled with complexity. Developers often piece together vector databases, memory stores, and orchestration tools to build agent systems, creating brittle, costly pipelines that are difficult to maintain. Some solutions offer forkable databases but stop short of supporting full environment replication. Others rely on proprietary architectures that lock teams into vendor ecosystems.
Agentic Postgres takes a different approach. Built on Postgres compatibility, it allows developers to leverage the mature Postgres ecosystem while gaining access to Tiger’s next-generation storage layer. The result is a platform that offers the speed, safety, and scalability agents require without sacrificing portability or performance.
The system is now available through Tiger’s new free tier, which gives developers hands-on access to forkable databases, hybrid search, memory APIs, and MCP integration at no cost. The goal: let teams experience the benefits of forkable infrastructure firsthand, then scale seamlessly into production.
A Database for Billions of Agents
Tiger Data’s latest launch marks a defining moment in database evolution. Just as the company built the foundation for IoT connectivity a decade ago, it now aims to power the next computing shift, from billions of devices to billions of intelligent agents.
As Tiger Data puts it: “For the agent era, the database is Tiger.”
