TigerData, the innovative team behind TimescaleDB and Tiger Postgres, has unveiled the groundbreaking Tiger Lake. This new architectural layer revolutionizes the data infrastructure, bridging the operational speed of Postgres with the analytical scale of the lakehouse. The launch of Tiger Lake opens up a world of new possibilities, addressing the tension of unifying live application data with deeper insights without the constraints of brittle ETL, vendor lock-in, or technical compromise.
Rethinking the Data Stack
Tiger Lake turns Postgres into a real-time engine that seamlessly connects to Iceberg-backed lakehouses, enabling continuous, bidirectional data movement between operational databases and scalable cloud storage systems.
“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.”
Unified Architecture Without Pipelines
At its core, Tiger Lake eliminates the traditional boundaries between systems built for transactions and those built for analytics. Instead of duplicating data across layers or relying on complex pipelines, developers can utilize Postgres and Iceberg as two components of a single, unified system: Postgres for fast ingestion and transformation, and Iceberg for historical queries, machine learning features, and more in-depth aggregations.
Tiger Lake is built directly into Tiger Postgres, TigerData’s enhanced version of PostgreSQL, designed for real-time and agentic workloads. Backed by TimescaleDB, Tiger Postgres handles high-ingest, time-series data with support for fast rollups and concurrent analytical queries at scale. This robust foundation gives Tiger Lake a production-ready base, instilling confidence in its ability to operate seamlessly under real-world demands.
A Real-Time System That Works Both Ways
The architecture supports continuous replication of Postgres tables into the lakehouse without manual ETL, Kafka streaming, or custom connectors. Crucially, Tiger Lake also supports syncing processed results from the lakehouse back into Postgres, making it possible to query enriched features, semantic rollups, or ML outputs from within the operational database.
“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.”
Early adopters like Speedcast and Monte Carlo are already using Tiger Lake to simplify previously complex data stacks, proving its readiness to support production-grade, real-time intelligence without compromise.
Open Standards, Not Lock-In
Tiger Lake reflects a larger shift in the industry toward composable, open data systems. Unlike platforms that lock users into tightly coupled, all-in-one stacks, Tiger Lake is built on open formats, such as Apache Iceberg, and integrates with standard cloud infrastructure. This provides engineering teams with the flexibility to adopt and evolve their architecture without being forced into proprietary control planes.
Public Beta and What’s Next
Tiger Lake is now available in public beta through Tiger Cloud. The initial release allows users to stream Postgres tables and TimescaleDB hypertables into Iceberg-backed S3 storage and to pull data back into Postgres.
Future updates will expand support to include querying Iceberg catalogs directly from within Postgres and full round-trip sync workflows that return computed insights into the operational layer.
A New Default for Intelligent Applications?
According to the company, this is just the beginning of a roadmap focused on reducing the friction between live context and analytical depth. By providing developers with a unified foundation for delivering application data and insights, Tiger Lake can set a new standard for building intelligent applications without delays, pipelines, or compromise.
