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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 Tiger Data?

Tiger Data is a next-generation PostgreSQL++ platform engineered for developers, devices, and AI agents that need scalable, intelligent data systems. As the company behind TimescaleDB, it extends PostgreSQL into a universal foundation for time-series analytics, real-time observability, AI retrieval, and agentic applications. The platform’s modular design introduces key primitives — Interface, Forks, Memory, Search, Materialization, and Scale — which collectively empower developers to build, deploy, and automate data-intensive workloads with ease. With Forks, users can instantly clone environments for testing or development, while Memory ensures contextual persistence across agents and time. Its hybrid search engine merges BM25 ranking with vector retrieval, enabling semantic and structured queries within a single system. Built-in time-series and streaming support allows sub-second analytics on billions of rows, while continuous aggregates and columnar compression optimize performance and cost. Tiger Cloud offers a fully managed deployment with multi-AZ resilience, encryption, SSO, and tiered storage for maximum efficiency. From IoT telemetry and financial data to AI observability and agent context storage, Tiger Data unifies real-time and analytical workloads under one Postgres-compatible umbrella. Companies like Cloudflare, Toyota, Polymarket, and Hugging Face rely on Tiger to simplify their infrastructure while scaling insights globally. With over 20,000 developers and a 4.7 G2 score, Tiger Data defines the future of PostgreSQL — smarter, faster, and built for the next era of intelligent systems.

What is Amazon Timestream?

Amazon Timestream is a fast, scalable, and serverless database solution specifically built for handling time series data, tailored for IoT and operational needs, enabling users to store and analyze trillions of events each day with speeds up to 1,000 times quicker and at a fraction of the cost compared to conventional relational databases. It effectively manages the lifecycle of time series data by keeping the most recent data in memory while transferring older information to a more cost-effective storage layer based on user-defined settings, which results in significant time and cost savings. The service's distinctive query engine allows users to access and analyze both current and historical data seamlessly, eliminating the need to specify the storage tier of the data being queried. Furthermore, Amazon Timestream is equipped with built-in analytics capabilities for time series data, enabling users to identify trends and patterns nearly in real-time, thereby improving their decision-making processes. This array of features positions Timestream as an excellent option for businesses aiming to utilize time series data effectively, ensuring they remain agile in a fast-paced data-driven environment. As organizations increasingly rely on data analytics, Timestream's capabilities can provide a competitive edge by streamlining data management and insights.

Media

Media

Media

Integrations Supported

APERIO DataWise
Grafana Cloud
PostgreSQL
Amazon S3
DataClarity Unlimited Analytics
HighByte Intelligence Hub
LangChain
Last9
Llama
Mode
MyDBA.dev
NexClipper
QStudio
Rackspace Cloud Files
SQL
Seeq
Tableau
TimescaleDB
Visplore
Wyn Enterprise

Integrations Supported

APERIO DataWise
Grafana Cloud
PostgreSQL
Amazon S3
DataClarity Unlimited Analytics
HighByte Intelligence Hub
LangChain
Last9
Llama
Mode
MyDBA.dev
NexClipper
QStudio
Rackspace Cloud Files
SQL
Seeq
Tableau
TimescaleDB
Visplore
Wyn Enterprise

Integrations Supported

APERIO DataWise
Grafana Cloud
PostgreSQL
Amazon S3
DataClarity Unlimited Analytics
HighByte Intelligence Hub
LangChain
Last9
Llama
Mode
MyDBA.dev
NexClipper
QStudio
Rackspace Cloud Files
SQL
Seeq
Tableau
TimescaleDB
Visplore
Wyn Enterprise

API Availability

Has API

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$30 per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Tiger Data

Date Founded

2015

Company Location

United States

Company Website

www.tigerdata.com/timescaledb

Company Facts

Organization Name

Tiger Data

Date Founded

2015

Company Location

United States

Company Website

www.tigerdata.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/timestream/

Categories and Features

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

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