{"id":299991,"date":"2025-06-18T03:11:44","date_gmt":"2025-06-18T03:11:44","guid":{"rendered":"https:\/\/peraltafinancing.com\/uncategorized\/from-timescale-to-tigerdata-signals-a-bold-future-for-postgresql\/"},"modified":"2025-06-18T03:11:44","modified_gmt":"2025-06-18T03:11:44","slug":"from-timescale-to-tigerdata-signals-a-bold-future-for-postgresql","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=299991","title":{"rendered":"From Timescale to TigerData: Signals a Bold Future for PostgreSQL"},"content":{"rendered":"


\n<\/p>\n

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TigerData<\/span><\/a>, the new name for Timescale, has officially unveiled its transformation into what it calls the \u201cfastest PostgreSQL platform for modern workloads.\u201d The move isn\u2019t just cosmetic. It signals a profound evolution in how the company views its mission: to help developers build real-time, agent-based, and analytical applications, all on the foundation of PostgreSQL.<\/span><\/p>\n

\u201cModern applications don\u2019t fit neatly into traditional database categories,\u201d said Ajay Kulkarni, Co-founder and CEO of TigerData. \u201cThey capture vast streams of data, power real-time analytics, and increasingly rely on intelligent agents that reason and act. These workloads\u2014transactional, analytic, and agentic\u2014require a new kind of operational database. That\u2019s exactly what we\u2019ve built at TigerData: a system that delivers speed without sacrifice.\u201d<\/span><\/p>\n

Formerly known as Timescale, the company made its mark by extending PostgreSQL for time-series and real-time analytics. But its ambitions have expanded. Today, TigerData supports over 2,000 customers across more than 25 countries and manages over 3 million active databases globally. Their journey from Timescale to TigerData is a testament to their growth and commitment to providing innovative solutions to customers.<\/span><\/p>\n

\u201cPostgreSQL, Reimagined\u201d<\/span><\/h2>\n

\"TigerData<\/p>\n

PostgreSQL may be the most popular operational database today, but TigerData is betting it needs a serious overhaul to meet modern demands. According to the company, it has evolved PostgreSQL without forking it, enabling developers to build faster, smarter applications without abandoning the ecosystem they already trust.<\/span><\/p>\n

That includes everything from horizontal scaling and 100+ petabyte compression to hybrid row-columnar engines and low-latency vector search. These capabilities come to life through <\/span>Tiger Cloud<\/span><\/a>, its cloud-native platform.<\/span><\/p>\n

TigerData\u2019s features are more than theoretical. \u201cThese aren\u2019t experimental features. They\u2019re running in production at a global scale\u2014today,\u201d the company emphasizes in its release, showcasing its reliability and trustworthiness.<\/span><\/p>\n

Lakehouse Meets Operational Database<\/span><\/h2>\n

TigerData is also making a significant bet on unifying operational and analytical data, two worlds that have traditionally remained siloed. The company is building continuous, high-throughput sync between <\/span>real-time systems and lakehouse architectures<\/span><\/a>, allowing developers to query across both using standard SQL.<\/span><\/p>\n

Industry leaders already rely on the platform for diverse, high-impact use cases. Lucid Motors uses TigerData to process real-time telemetry for autonomous driving. Hugging Face and Mistral depend on it for agent-grade AI infrastructure. Financial institutions like Barclays and publishers like the Financial Times use it to drive time-sensitive analytics and semantic search.<\/span><\/p>\n

This wide-ranging adoption speaks to TigerData\u2019s growing presence across industries\u2014from AI and fintech<\/a> to industrial IoT and media. Its ability to handle both high-ingest workloads and advanced analytical queries gives it a unique edge.<\/span><\/p>\n

Investor Confidence and What Comes Next<\/h2>\n

Backing up its momentum is strong investor confidence. TigerData is backed by $180 million from top-tier investors, fueling its continued innovation and expansion. That capital supports its mission to push PostgreSQL into the future and cement its place as the data layer of modern applications. The funding also signals broader market validation for its hybrid database approach, as enterprises increasingly seek unified platforms that can support analytics, transactions, and AI-native workflows in one system.<\/span><\/p>\n

Looking further ahead, TigerData is pioneering \u201cAgentic PostgreSQL,\u201d a vision of database infrastructure that integrates memory, retrieval, and reasoning as first-class features. This is a clear demonstration of the company\u2019s forward-thinking approach and commitment to innovation.<\/span><\/p>\n

What\u2019s in a Name?<\/span><\/h2>\n

The rebrand from Timescale to TigerData encapsulates a broader vision. What began as a tool for time-series data is now positioning itself as the backbone of modern data infrastructure, spanning real-time analytics, AI agents, and intelligent search. This rebranding is not just a change in name, but a strategic move to better reflect their expanded capabilities and the value we bring to customers.<\/span><\/p>\n

As Kulkarni put it, \u201cSpeed, flexibility, and simplicity\u2014delivered together, on a foundation they already trust: PostgreSQL.\u201d<\/span><\/p>\n

\u00a0<\/p>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

TigerData, the new name for Timescale, has officially unveiled its transformation into what it calls the \u201cfastest PostgreSQL platform for modern workloads.\u201d The move isn\u2019t just cosmetic. 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