In today’s data-driven world, enterprises face unprecedented pressure to manage diverse workloads, from real-time IoT streams to AI-powered decision-making, without compromising scalability, performance, or familiarity. The surge of operational and experimental data has highlighted a critical need: modern infrastructure that unifies developers, devices, and AI agents on a single platform.
Recognizing this challenge, Tiger Data, the company behind TimescaleDB and Agentic Postgres, has announced a strategic collaboration agreement (SCA) with Amazon Web Services (AWS). The partnership promises to accelerate the delivery of modern data infrastructure built on Postgres, providing a seamless experience across analytics, AI, and operational systems.
“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 Integration for Developers
At the heart of the collaboration is a deep integration with AWS services. Tiger Data already supports turnkey connections to Amazon Athena, Amazon Redshift, Amazon QuickSight, and Amazon SageMaker, enabling developers to query operational data and lakehouse analytics using the same SQL interface. The SCA expands these capabilities through joint development efforts, broader availability on AWS Marketplace, and co-investments in technical enablement and customer success programs.
For enterprises, this means they can consolidate operational data on Postgres while tapping into the full suite of AWS analytics and AI services. The platform also supports the streaming of data from Postgres to Apache Iceberg on Amazon S3 in seconds, ensuring a single, governed source of truth for dashboards, analytics, and AI/ML workloads. More details are available through Tiger Data on AWS.
Infrastructure Tailored for AI Agents
As AI agents transition from tools to autonomous collaborators, they demand database primitives that enable rapid experimentation without disrupting production systems. Tiger Data’s Agentic Postgres addresses this need, allowing developers and AI agents to create instant, zero-copy environments. Agents can run parallel experiments, test workflows, and scale operations while preserving data integrity.
Unified Architecture for Operational Data
Tiger Data’s Postgres platform is optimized for high-volume time-series and event data, offering billions of writes, low-latency queries, and automatic compression. The combination of resilient Postgres and AWS analytics infrastructure enables businesses to manage IoT, Web3, and AI workloads seamlessly. Tiger Cloud, available through AWS Marketplace, already powers more than 2,000 customers in production environments, from automotive and industrial applications to AI research platforms.
Building the Modern Data Architecture
The Tiger Data-AWS collaboration reflects a broader industry trend: unifying disparate workloads under a single, scalable, and developer-friendly infrastructure. By integrating deeply with AWS services, supporting AI agents with Agentic Postgres, and delivering robust operational data capabilities, the partnership provides a blueprint for the next generation of Postgres-based infrastructure. For organizations looking to modernize their data stack, platforms like Tiger Cloud offer a proven path to production-ready, scalable solutions for developers, devices, and AI agents alike.