Timescale has always been more than a time-series database. Over the past eight years, it transformed PostgreSQL into a platform of breathtaking speed, scale, and versatility. Now, that transformation is front and center. In June 2025, Timescale officially rebranded as TigerData, a change that reflects not just a new name but the company’s evolution into a leader in modern, analytical, and agentic workloads in PostgreSQL ecosystems.
The rebrand is grounded in substance. TigerData now boasts a thriving business with around 2,000 customers, a mid-eight-digit annual recurring revenue (ARR), over 100% year-on-year growth, and roughly $180 million raised from top investors. The company supports AI-native giants like Mistral and HuggingFace, as well as global leaders such as NVIDIA and Toyota, and innovators like NASA, JP Morgan Chase, and Tesla.
From Time-Series to the Broader Frontier
In the early days, Timescale’s mission was unambiguous: to bring time-series capabilities to PostgreSQL. Despite skeptics who dismissed SQL databases as outdated compared to NoSQL rising stars like MongoDB, Cassandra, or InfluxDB, the company’s dedication to its mission, bolstered by consistent engineering and compelling proof points, swung perception, and PostgreSQL began to regain its luster.
This momentum paved the way for TigerData’s current identity: “The fastest PostgreSQL,” purpose-built not just for time-series workloads but for a broader spectrum of operational and analytical demands. Agentic systems with agents that observe, decide, and act are now mainstream, and TigerData’s performance, scale, and architectural depth make it a natural backbone for those applications.
Architectural Excellence: Powering Performance at Scale
TigerData isn’t just a rebrand, but an embodiment of a refined PostgreSQL platform. At its architectural heart lies a fusion of hypertables, hybrid row-columnar storage, vectorized execution, continuous aggregates, hyperfunctions, and cloud-native infrastructure.
Hypertables enable automatic partitioning that scales seamlessly as data volumes grow. At the same time, hybrid “Hypercore” storage ensures both fast ingest (via rowstore) and high-performance analytics (via columnar store with up to 95% compression). Continuous aggregates and hyperfunctions shrink latency for complex analytical queries by precomputing and optimizing runtime computations.
On the operational side, the newly rebranded cloud service Tiger Cloud is designed with independent scaling of compute and storage, workload isolation, intelligent data, tiering to object storage, observability tooling, high-availability replicas, connection pooling, backups, and point-in-time recovery. This results in real-time analytics and low-latency queries without sacrificing PostgreSQL reliability.
Customer Stories: Real Impact, Real Results
Concrete customer use cases resonate: Polymarket used TigerData to scale up fourfold during elevated election trading, facilitating over $3.7 billion in trades. Linktree leveraged TigerData to shrink the launch time of analytical features from two weeks to just two days, saving $17,000 per month while compressing 12.6 TB of data. Meanwhile, Evergen, an Australian renewable energy platform, transitioned from MongoDB to TigerData. They gained real-time telemetry, centralized time-series handling, logical transformations, SQL accessibility for broader teams, and sustainable scalability. These success stories are a testament to the company’s commitment to customer success.
Community, Culture, and Identity: Why “Tiger”?
Why TigerData? The tiger has been the company’s mascot since 2017, emblematic of speed, power, and precision. It evolved into cultural rituals, such as “Tiger Time” weekly all-hands, “State of the Tiger” reviews, calling new hires “tiger cubs,” and referring to the business as “the jungle.” The rebrand is crystallizing what the company already represents.
The New Era of TigerData
TigerData represents not just a name change, but an affirmation of its journey. From the early days of being the audacious time-series extension atop PostgreSQL, it has grown into a full-fledged analytical powerhouse, trusted by market leaders and innovators. The TigerData launch isn’t about erasing what Timescale was, but signaling the company’s expanded mission: delivering speed without sacrifice for the modern, analytical, agentic era.