TigerData Introduces Tiger Lake: A Native Bridge Between Postgres and the Lakehouse

TigerData, the company behind TimescaleDB and Tiger Postgres, has announced the launch of Tiger Lake, a new architecture aimed at solving one of the most significant challenges in modern data systems: unifying fast operational data with scalable analytical infrastructure.

Built as a native, bidirectional bridge between PostgreSQL and Iceberg-backed lakehouses, Tiger Lake enables data to flow continuously between transactional databases and open data lakes without relying on fragile ETL pipelines, vendor lock-in, or architectural trade-offs.

"Postgres has become the operational heart of modern applications, but until now, it's existed in a silo from the lakehouse," said Mike Freedman, co-founder and CTO of TigerData. "With Tiger Lake, we've built a native, bidirectional bridge between Postgres and the lakehouse. It's the architecture we believe the industry has been waiting for."

Eliminating the Divide Between Systems

Tiger Lake transforms Tiger Postgres, a real-time PostgreSQL enhanced by TimescaleDB, into the operational backbone of the open lakehouse. This enables teams to use one system for high-ingest, low-latency workloads and another for long-term analytical queries, all while maintaining sync between the two.

Instead of relying on fragile orchestration layers or deferred ETL jobs, Tiger Lake offers real-time streaming and synchronization of data in both directions. Postgres tables can be continuously replicated into the lakehouse. At the same time, results generated in Apache Iceberg, such as ML features, downsampled metrics, or historical rollups, can be streamed back into Postgres for immediate use in live applications.

According to Freedman, the goal is architectural cohesion without compromise: "Tiger Lake unifies both, natively and without compromise."

Simplifying Complexity for Developers

In practice, many engineering teams have had to cobble together solutions using multiple tools, such as Kafka, Flink, and hand-rolled pipelines. For Kevin Otten, Director of Technical Architecture at Speedcast, Tiger Lake represents a welcome shift.

"We stitched together Kafka, Flink, and custom code to stream data from Postgres to Iceberg---it worked, but it was fragile and high-maintenance," Otten said. "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."

Speedcast isn't alone, as other forward-thinking organizations are already deploying Tiger Lake in production to simplify infrastructure and accelerate time-to-insight.

By removing the complexity and fragility from these systems, Tiger Lake provides a sense of reassurance to developers. It enables them to focus on building intelligent, responsive applications, rather than debugging brittle integrations.

Powered by Open Standards

Tiger Lake works by connecting Postgres to the lakehouse through open standards such as Apache Iceberg, offering compatibility with AWS S3 Tables and broad interoperability across the data ecosystem.

The emphasis on open infrastructure stands in contrast to all-in-one platforms that bind users to proprietary runtimes and control planes. TigerData positions Tiger Lake as a modular, future-proof alternative that offers the flexibility to integrate with a range of query engines, ML systems, and observability tools.

"Tiger Lake keeps Postgres and Iceberg open, composable, and future-proof," according to the company's launch announcement. This modularity allows developers to retain full control over their architecture while scaling intelligently, providing a sense of security.

From Beta to What's Next

Tiger Lake is now available in public beta, fully managed through Tiger Cloud, starting today. The initial release includes support for streaming Postgres tables and TimescaleDB hypertables into AWS S3 Tables using the Iceberg format. It also enables streaming from Iceberg-backed S3 files back into Postgres.

In the future, TigerData plans to enhance Tiger Lake's capabilities. This includes supporting direct querying of Iceberg catalogs from within Postgres and enabling round-trip sync of Iceberg-derived outputs, such as aggregates or machine learning features, into operational workflows.

A New Default for Intelligent Applications?

With Tiger Lake, TigerData hopes to set a new standard for modern application architecture. By uniting the responsiveness of Postgres with the analytical depth of the lakehouse, Tiger Lake natively enables developers to build real-time, intelligent applications that are both faster to ship and easier to maintain.

Or as Otten put it: "It's the architecture we wish we had from day one."