TigerData Emerges as the Fastest PostgreSQL Platform for a New Era of Data-Driven Applications

Timescale, long known for pioneering time-series capabilities in PostgreSQL, has rebranded as TigerData in a bold move that signals its transformation into a platform purpose-built for today's real-time, data-intensive, and AI-driven applications.

The change reflects more than a name. It marks a strategic shift. TigerData is now positioning itself as the fastest PostgreSQL platform designed for what it calls "agentic workloads": applications that blend transactional processing, real-time analytics, and intelligent agents that can dynamically retrieve and reason over data. With more than 2,000 customers in 25+ countries and over 3 million active databases, the company is solidifying its position at the core of modern infrastructure.

"Modern applications don't fit neatly into traditional database categories," said Ajay Kulkarni, co-founder and CEO of TigerData. "They capture vast streams of data, power real-time analytics, and increasingly rely on intelligent agents that act on that data. These workloads demand speed without compromise---and that's what TigerData delivers."

From TimescaleDB to Tiger Cloud

TigerData's foundation was laid with TimescaleDB, an open-source PostgreSQL extension that introduced native support for time-series and high-ingest workloads. But in the years since, the company has quietly evolved its platform into a fully cloud-native data stack designed to meet far more complex demands.

The result is Tiger Cloud, a managed PostgreSQL service that integrates features like horizontal scalability, petabyte-scale compression, hot/cold data tiering, and deep observability. Unlike vendors that fork PostgreSQL to build new functionality, TigerData has remained true to the upstream project while dramatically expanding its capabilities.

Key innovations include Hypertables for automatic time-based partitioning, Continuous Aggregates for real-time materialized views, and Hypercore, a hybrid row-columnar engine optimized for lightning-fast, user-facing analytics. Together, these features allow developers to build fast, intelligent applications without switching between different databases for different workloads.

Powering Agentic Applications at Scale

Where TigerData sets itself apart is in its embrace of the emerging agentic computing paradigm. As AI agents become integral to application logic, the underlying database must evolve to support low-latency retrieval, dynamic memory, and embedding-based search. TigerData has engineered its platform accordingly.

It now supports vector search with Streaming DiskANN and HNSW, as well as SQL-native embedding pipelines with freshness guarantees, and retrieval tools designed for reasoning-based applications. These aren't experimental features, but they're already running in production at scale.

Companies like Hugging Face and Mistral use TigerData to support production-grade AI systems. Automotive firm Lucid Motors relies on the platform for real-time telemetry and autonomous analytics. Even legacy industries are on board: the Financial Times and Barclays use TigerData for fast semantic search and operational intelligence, while the European Space Agency and Schneider Electric employ it for industrial IoT monitoring.

Looking Ahead: A Database for Agents and Humans

TigerData is now building toward its next act: a new high-performance storage engine featuring compute-local caching, disaggregated replicas, and zero-copy branching, optimized for extreme ingest and replay workloads. As lakehouse architectures gain traction, the company is also developing a continuous sync layer between operational and historical data, allowing developers to query both seamlessly through PostgreSQL.

Most ambitiously, TigerData is laying the groundwork for Agentic PostgreSQL---a future where memory and reasoning are embedded directly into the database engine, making it possible to build applications that think and adapt independently.

With $180 million in funding and a sharp focus on speed, simplicity, and scale, TigerData isn't just building a faster PostgreSQL. It's redefining what a modern operational database can be.