A new architecture that connects operational databases and open lakehouses to power customer-facing analytics and agents-without pipelines, lock-in, or compromise.
A New Class of Architecture for Real-Time Intelligence
NEW YORK CITY, NY / ACCESS Newswire / July 17, 2025 / TigerData, creators of Tiger Postgres and the team behind TimescaleDB, today announced Tiger Lake-a bold new architecture that transforms Postgres into the operational backbone of the open lakehouse. Starting with support for Amazon Simple Storage Service (Amazon S3) Tables, fully-managed, purpose-built S3 storage that is optimized for storing, managing, and querying Apache Iceberg tables at scale. Tiger Lake eliminates brittle pipelines and fragmented stacks, giving developers a modular, bidirectionally synced system: Postgres becomes the real-time engine for operational workloads, while Iceberg-backed lakehouses provide scalable deep analytics.
Photo credit: TigerData
This launch signals a shift toward open, real-time infrastructure where Postgres and the lakehouse operate in tandem, not in isolation. Instead of relying on fragile syncs or deferred ETL, Tiger Lake delivers continuous data movement and enrichment across the entire stack.
“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.”
Postgres Meets the Lakehouse, Without Pipelines or Lock-In
Other approaches force a choice between real-time performance and analytical depth. Tiger Lake unifies both, natively and without compromise.
Tiger Lake is a built-in capability of Tiger Postgres-TigerData’s enhanced PostgreSQL, powered by TimescaleDB and purpose-built for real-time analytics, time-series, and agentic workloads. While other offerings split between transactional systems or batch analytics engines, Tiger Postgres unifies both, handling high-ingest, real-time rollups, time-series workloads, and fast, concurrent queries at scale. Most systems weren’t built to serve real-time analytics from operational data. Tiger Postgres was. And unlike emerging lakehouse databases that struggle with production readiness, Tiger Lake builds on mature, hardened infrastructure with a proven developer base.
With Tiger Lake, developers can continuously replicate any Postgres table into the lakehouse, without custom pipelines or fragile orchestration layers. At the same time, Tiger Postgres remains the system of record for operational data, powering real-time ingestion, transformations, and rollups at the point of generation. And when deeper insights are computed in Iceberg-such as historical aggregates, ML features, or downsampled metrics-Tiger Lake syncs those results back into Postgres, where they’re ready to serve in applications, dashboards, and agents.
This bidirectional architecture provides a unified model where data flows both ways between database and lakehouse. It combines the speed and precision of Postgres with the scale and flexibility of Iceberg-without duplication, lock-in, or compromise.
This architecture enables a powerful new pattern for real-time applications-from agents to customer-facing analytics. It provides real-time, low-latency access to analytical insights, operational events, and enriched features, without waiting on ETL or manual syncs. Whether powering agents, copilots, or customer-facing dashboards, Tiger Lake lets developers query historical results, ML features, and semantic summaries directly from Postgres, using familiar tools and infrastructure. It bridges the gap between live application context and deep analytical history, unlocking the intelligent behavior modern applications demand.
“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.”
Built on Open Standards, Made for Composable Systems
Tiger Lake connects Postgres to the lakehouse using open formats like Apache Iceberg, avoiding proprietary runtimes or custom metadata layers. Developers can integrate with the wider data ecosystem-query engines, ML pipelines, observability tools-without being boxed into a single vendor’s stack.
This openness stands in contrast to tightly-integrated yet closed data platforms, where storage, compute, and query are fused into a single control plane. With Tiger Lake, developers retain modularity and control; they can choose the best components for the job, from Amazon S3 Tables to Spark to Snowflake.
Whereas others promote “end-to-end” stacks that lock you into proprietary runtimes, Tiger Lake keeps Postgres and Iceberg open, composable, and future-proof.
Tiger Lake works natively with Amazon S3 Tables, making it easy to manage Iceberg data using familiar Amazon S3 tools and APIs.
Innovative brands such as Speedcast, Lumia Health, and Pfeifer & Langen are already deploying Tiger Lake, starting with native support for Amazon S3 Tables.
Available Today, With a Roadmap to Full Round-Trip Sync
Tiger Lake is available in public beta today, fully managed on Tiger Cloud, with an initial focus on streaming Postgres tables and TimescaleDB hypertables from Tiger Postgres into Amazon S3 Tables using the Iceberg format, and streaming data from S3 files to Postgres.
Planned enhancements include querying Iceberg catalogs directly from within Tiger Postgres and full round-trip sync workflows that bring Iceberg-computed results (like aggregates or features) back into Postgres for real-time serving.
Together, these capabilities offer a unified, open foundation for building real-time and intelligent applications-without giving up control or composability.
About TigerData
TigerData is the company behind TimescaleDB and Tiger Postgres, the fastest PostgreSQL for real-time, analytical, and agentic applications. As an AWS Partner with solutions available on AWS Marketplace, TigerData helps more than 2,000 customers-including Warner Music, HuggingFace, Mistral, Linktree, and Postman-build intelligent applications using fully managed PostgreSQL infrastructure. Founded in 2017, TigerData has raised over $180 million from investors including Benchmark, NEA, Redpoint, and Tiger Global.
Media Contact:
Omri Hurwitz
TigerData
[email protected]
https://www.tigerdata.com/
SOURCE: TigerData
