Enterprises today face a mounting challenge: managing enormous volumes of operational data while ensuring performance, reliability, and ease of use. From IoT sensors streaming real-time telemetry to Web3 platforms and AI-driven applications, organizations need infrastructure that can scale without forcing developers to abandon familiar tools. Tiger Data, the company behind TimescaleDB and Agentic Postgres, has partnered with Amazon Web Services (AWS) to tackle this challenge head-on, delivering modern data infrastructure built on Postgres.
The strategic collaboration agreement (SCA) brings together three critical workloads: traditional developer applications, device-generated operational data, and AI agents that act as autonomous co-developers. By unifying these workloads on a single Postgres-based platform, Tiger Data and AWS aim to simplify complex data operations while enabling faster experimentation and innovation.
“The future of data infrastructure isn’t about specialized systems for every workload,” said Ajay Kulkarni, CEO and co-founder of Tiger Data. “It’s about a unified infrastructure that handles what developers build, what devices generate, and what agents need to operate—all on Postgres. With AWS, we’re making that architecture real, with integrations that connect Postgres to the full AWS stack, and the performance that makes it production-ready at scale.”
Deep AWS Integrations
Tiger Data’s platform already offers native connections to Amazon Athena, Amazon Redshift, Amazon QuickSight, and Amazon SageMaker, allowing developers to query operational and analytics data from a single SQL interface. The collaboration seeks to expand these integrations, increase availability via AWS Marketplace, and co-invest in technical enablement and customer success initiatives. Enterprises can explore Tiger Data on AWS to leverage this unified architecture for both transactional and analytical workloads.
Agentic Postgres: Infrastructure for AI Agents
One of the most forward-looking aspects of this partnership is Tiger Data’s Agentic Postgres platform. AI agents, increasingly deployed as co-developers and decision-makers, require ephemeral, zero-copy environments to experiment, test workflows, and operate at scale without impacting production. Agentic Postgres provides exactly this capability, enabling rapid iteration and autonomous operation. By combining this with AWS’s analytics and AI services, organizations can support intelligent, adaptive systems in real-time.
Unified Architecture for Operational Data
Tiger Data’s Postgres infrastructure is optimized for high-throughput, time-series, and event-driven workloads. It handles billions of writes, offers low-latency queries, and automatically compresses data for efficiency. Real-time streaming to Apache Iceberg on Amazon S3 creates a single, governed source of truth for dashboards, analytics, and AI/ML workloads.
Tiger Cloud, Tiger Data’s managed platform, powers over 2,000 customers across IoT, Web3, and AI, providing a reliable foundation for production workloads. Organizations can experiment with Tiger Cloud to see how a unified Postgres architecture can transform their operational data strategy.
A Blueprint for the Future of Data Infrastructure
As enterprises grapple with fragmented systems and specialized workloads, the Tiger Data and AWS collaboration offers a compelling alternative: unified, scalable, and developer-friendly data infrastructure built on Postgres. By bridging developer applications, device data, and AI agents, this partnership is helping organizations reduce complexity, improve governance, and accelerate innovation. The SCA is a technology agreement and a blueprint for the next generation of enterprise data architecture.
