Timescale
TigerData is the fastest PostgreSQL platform designed for real-time analytics, time series, and AI vector workloads. It offers a cloud-based managed PostgreSQL service called Tiger Cloud, providing speed, scale, and simplicity for demanding customer-facing production applications. The company is the creator of TimescaleDB and pgvectorscale, delivering features like hypertables for efficient data partitioning, continuous aggregates, data tiering, and point-in-time recovery. Trusted by over 2,000 companies with 3 million active databases, TigerData supports industries such as manufacturing, fintech, agriculture, and SaaS. It provides enterprise-grade security, compliance (SOC2, GDPR, HIPAA), and reliability with managed encryption, VPC peering, and automatic failovers. TigerData is backed by $180 million in funding and led by experienced founders Ajay Kulkarni and Mike Freedman.
Timescale
TigerData is the fastest PostgreSQL platform designed for real-time analytics, time series, and AI vector workloads. It offers a cloud-based managed PostgreSQL service called Tiger Cloud, providing speed, scale, and simplicity for demanding customer-facing production applications. The company is the creator of TimescaleDB and pgvectorscale, delivering features like hypertables for efficient data partitioning, continuous aggregates, data tiering, and point-in-time recovery. Trusted by over 2,000 companies with 3 million active databases, TigerData supports industries such as manufacturing, fintech, agriculture, and SaaS. It provides enterprise-grade security, compliance (SOC2, GDPR, HIPAA), and reliability with managed encryption, VPC peering, and automatic failovers. TigerData is backed by $180 million in funding and led by experienced founders Ajay Kulkarni and Mike Freedman.
TL;DR
Founded: 2015
Core product: TimescaleDB — a PostgreSQL-based time-series database (open source) with a managed cloud offering
Founders: Ajay Kulkarni (CEO) and Michael Freedman (CTO)
Funding: $180M total; Series C (Feb 2022) led by Tiger Global
Technical strengths: Hypertables, continuous aggregates, data tiering, point-in-time recovery, vector workloads (pgvectorscale)
Company Overview
Problem Domain
Time-series databases, real-time analytics, high-ingest telemetry/IoT and cloud-managed database services
Founded
2015
Industry
Databases
Tech Stack
Funding Track Record
$12.4M
$15M
Described as an extension of the prior Series A
$40M
Company reported ~ $70M total raised at this time
$110M
Reported valuation of $1.0B (Dealroom)
Investor Signal
“Backed by Benchmark, NEA, Two Sigma Ventures, Icon Ventures, Redpoint, and Tiger Global”