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What is TimescaleDB?

TimescaleDB is an advanced time-series and analytics database built entirely on top of PostgreSQL, combining the best of relational reliability and time-series speed. It’s engineered to help developers and data teams analyze streaming, sensor, and event data in real time, while retaining historical data cost-effectively. Its core innovation, the hypertable, automatically partitions large datasets across time and space, optimizing query planning and ingestion for billions of records. TimescaleDB’s continuous aggregates provide incrementally refreshed views, enabling instant dashboards and analytics without costly recomputations. It also offers hybrid row-columnar storage, blending transactional speed with analytical performance, and supports compression rates up to 95% for long-term data storage. With built-in automation for retention, aggregation, and reordering, it reduces the operational overhead of managing time-series data at scale. TimescaleDB’s hyperfunctions library extends SQL with over 200 specialized time-series analysis functions — ideal for anomaly detection, forecasting, and performance tracking. Because it’s 100% PostgreSQL compatible, teams can leverage existing Postgres tools, drivers, and extensions while gaining time-series capabilities instantly. Open-source and cloud-ready, it powers critical workloads for industries ranging from IoT and fintech to cloud infrastructure monitoring. With TimescaleDB, developers can query billions of data points in milliseconds — using the same SQL they already know.

What is PipelineDB?

PipelineDB acts as an enhancement to PostgreSQL, enabling the effective aggregation of time-series data specifically designed for real-time analytics and reporting needs. It allows users to create continuous SQL queries that consistently compile time-series data while only saving the summarized results in conventional, searchable tables. This method resembles extremely efficient, self-updating materialized views that do not require manual intervention for refreshing. Importantly, PipelineDB does not write raw time-series data to disk, which significantly boosts the performance of aggregation operations. The continuous queries produce their own output streams, facilitating the easy integration of various continuous SQL processes into intricate networks. This capability guarantees that users can develop sophisticated analytics solutions that adapt in real time to incoming data, making it a powerful tool for data-driven decision-making. Moreover, the ability to link multiple data streams enhances the potential for comprehensive insights from diverse datasets.

Media

Media

Integrations Supported

PostgreSQL
APERIO DataWise
AccessOwl
DataClarity Unlimited Analytics
Dataplane
HighByte Intelligence Hub
Last9
Mode
MyDBA.dev
NexClipper
Opralog
QStudio
Tiger Data
TrendMiner
Visplore
Workers by Delos
Wyn Enterprise
n8n

Integrations Supported

PostgreSQL
Luzmo
Vertica

API Availability

API Availability

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

Tiger Data

Date Founded

2015

Company Location

United States

Company Website

www.tigerdata.com/timescaledb

Company Facts

Organization Name

PipelineDB

Company Location

United States

Company Website

github.com/pipelinedb/pipelinedb

Categories and Features

Relational Database

Not specified

Time Series Databases

Not specified

Categories and Features

Database

Data Security
Mobile Access
NOSQL
Performance Analysis
Queries
Relational Interface

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