By: Jake Smiths
In the age of AI agents, predictive analytics, and instant user experiences, the infrastructure behind modern applications is under pressure. Data can no longer sit in isolated systems, because real-time operations and analytical insights must flow seamlessly. That’s the promise behind TigerData’s latest move: native support for AWS S3 Tables.
The company, known for developing TimescaleDB and pushing the boundaries of PostgreSQL performance, announced this week that its Tiger Lake architecture now supports AWS S3 Tables. This feature allows developers to manage Apache Iceberg tables directly within Amazon S3 using open standards.
With this update, TigerData provides developers with a unified system where PostgreSQL and Iceberg-based lakehouses no longer exist in silos. Instead, they work together natively without brittle pipelines or expensive orchestration, streamlining how modern applications process and respond to data.
From Fragile Pipelines to Seamless Data Flows
In many organizations, syncing transactional data from databases like Postgres into analytical environments like Iceberg has required a mess of tools, such as Kafka, Flink, and layers of custom code. This complexity is hard to maintain and slows innovation.
“We stitched together Kafka, Flink, and custom code to stream data from Postgres to Iceberg—it worked, but it was fragile and high-maintenance,” said Kevin Otten, Director of Technical Architecture at Speedcast. “Tiger Lake replaces all of that with native infrastructure. It’s not just simpler—it’s the architecture we wish we had from day one.”
Tiger Lake, now available in public beta on Tiger Cloud, lets users stream any PostgreSQL table directly into Iceberg-backed S3 Tables. But it doesn’t stop there. It also supports bidirectional synchronization, enabling the output of Iceberg queries (such as aggregates or machine learning features) to flow back into Postgres in real-time. This tight feedback loop is crucial for powering use cases such as AI agents, semantic search, personalized dashboards, and live analytics.
A New Pattern for Next-Gen Applications
What makes Tiger Lake compelling isn’t just what it eliminates (pipelines, latency, operational overhead). It’s what it enables.
This architecture unlocks a new pattern that allows real-time operational context and deep historical insight to coexist in a single, low-latency environment. Developers can use familiar Postgres tools to access rich Iceberg datasets. Analytical summaries, behavioral features, and ML model outputs become accessible with every application interaction, eliminating the need to wait for batch ETL jobs.
Whether building AI copilots, real-time anomaly detection, or hyper-personalized user interfaces, teams gain a competitive edge by responding to live data with full context. As Postgres-native infrastructure increasingly powers intelligent applications, TigerData’s strategy positions it at the heart of this transition.
Toward a Modular, Open Future
This launch is also part of a broader industry trend: the move away from vertically integrated, monolithic data platforms toward modular architectures where systems operate as interconnected peers. Rather than treating operational databases and analytical lakehouses as separate domains, TigerData’s approach merges their capabilities under an open, standards-based umbrella.
That distinction matters. In a world where vendor lock-in and proprietary protocols often slow innovation, Tiger Lake offers developers choice, flexibility, and control. It combines Postgres’s speed and concurrency with Iceberg’s scalability and openness, without compromising performance or interoperability.
Built for the Age of Agents
As AI-native tools, copilots, and generative interfaces become mainstream, data infrastructure must evolve to meet their demands. This means making real-time decisions based not only on the last row in a database, but also on the entire analytical footprint of a user, system, or environment.
TigerData is making a strategic push toward this convergence. Backed by investors such as Benchmark, NEA, and Tiger Global, and with customers including Warner Music, Mistral, and Postman already building on its platform, the company is staking its future on a PostgreSQL-native foundation for intelligent applications.
With native AWS S3 Tables support and a clear architectural vision, TigerData isn’t just keeping pace with cloud innovation. It’s helping define what comes next.
