TimescaleDB System Properties

Tiger Data is the creator of TimescaleDB, the first open-source relational database for time-series data. TimescaleDB offers the reliability, flexibility, ease-of-use, and scalability that applications, data analytics infrastructure, and complex systems require.

All data is time-series data. Time-series data captures how information changes over time - website and infrastructure performance, financial tick data, and more - and TimescaleDB is the only relational database built with the performance, scalability, and reliability to store these relentless streams of data.

Tiger Data offers TimescaleDB as a hosted service through Tiger Cloud. Developers choose Tiger Cloud for many reasons, including:

• Worry-free operations. Hosted and managed by Tiger Data, freeing teams to focus on running their business and analyzing data, not managing data infrastructure.
• Complete flexibility. Scale your services in one click, with decoupled compute and storage pricing.
• Get started quickly. Launch your database in seconds, including multi-node services.

TimescaleDB at-a-glance

Supercharged Postgres

• Full SQL, no restrictions
• Rock-solid reliability and scalability
• Compatible with a vast ecosystem of extensions and tools

Accelerated Performance

• Get 10X faster inserts, 1,400X faster queries, and ingest 1.5M+ more metrics per second per server
• Speed up your aggregate queries to get real-time insights with continuous aggregates
• Downsample your dataset automatically to do fast analysis over historical data

Massive scale

• Store 100s of billions of rows & 10s of TBs of data per server
• Best-in-class datatype-specific compression algorithms for 16x storage capacity
• Create multi-node databases with distributed hypertables across many TimescaleDB nodes

Relational and time-series, together

• Correlate your time-series and business data
• Perform JOINs to understand relations with time-series
• Ensure clean, correct data with foreign keys and constraints

Worry-free operations

• Spin up a pre-configured instance in seconds
• Automated, continuous backups with point-in-time recovery
• Integrated metrics, logs, security and user controls

Lower costs

• Reduce storage costs with 94-97% lossless compression rates
• Decoupled storage and compute pricing
• Scale compute and storage in one click according to your needs

To get started, check out the Tiger Data Docs and the Tiger Data Slack Community.

TimescaleDB is purpose-built to scale and handle time-series data workloads and is intentionally designed as a PostgreSQL extension. Its features include:

• Native support for ANSI SQL, including JOINs with relational metadata that can be stored right in standard PostgreSQL tables
• time_bucket and gap_fill, allowing users to query data at any time interval (v. SQL limitations) and choose how they solve for NULL values and missing data
• GIS support (via PostGIS, another PostgreSQL extension) to roll your own geo-temporal database
• Support for ACID operations and transactions
• Secondary indexes, including composite indexes
• Secondary JOINs
• Transparent resource utilization and performance (e.g. many options for administration and tooling, offers the ability to run EXPLAIN, etc.)
• Native compression and real-time aggregation capabilities to reduce data stored on disk, while still allowing users to analyze historical data
• Automated data retention policies to remove the burden of manual data lifecycle management
• Integration with Grafana and Prometheus for data visualization and long-term data storage (roll your own IT Monitoring stack)

TimescaleDB combines the reliability and tooling of PostgreSQL with enterprise-grade security, production-ready SLAs, and community-based and professional support services.

TimescaleDB is also flexible and customizable, supporting thousands of extensions, products, and integrations critical for data analysis, including: Tableau, Looker, Mode, Grafana, PowerBI, Apache Kafka, RabbitMQ, Apache Spark, Prometheus, Zabbix, JDBC/ODBC, Telegraf, and more.

Time-series Analytics

TimescaleDB boosts the performance of PostgreSQL for time-series data, giving you significantly higher inserts and faster queries so you can drive real-time, user-facing dashboards for your data-intensive applications. On top of it, TimescaleDB expands SQL for time-series. Use hyperfunctions like time_bucket, gap_fill, or stats_agg to easily do complex analysis in SQL, define continuous aggregates to speed up your aggregate queries over high data volumes, and combine compression with data retention policies to automatically and progressively downsample your data once it reaches a certain age.

Internet of Things

Device and sensor data are time-series data: tracking device performance with pinpoint geospatial and temporal accuracy is a time-series problem. TimescaleDB helps you cost-effectively store and analyze relentless streams of device telemetry and sensor readings at scale, in order to manage industrial equipment maintenance, fleet management, asset tracking, route planning, yield optimization, oil and gas production, and more.

Web3 + Crypto

Whether you are analyzing the price of cryptocurrencies, tracking NFT sales, or monitoring blockchains, you are working with time-series data. Thanks to its combination of excellent ingestion and real-time capabilities with the ability to do historical data analysis, TimescaleDB is an optimal choice for web3 use cases. Features like time_bucket, continuous aggregates, and compression make it quick and easy to do complex analysis in SQL, while ingesting thousands of data points per second to feed real-time dashboards, and keeping the storage costs low.

Observability

Observability data is time-series data. By using Promscale, the observability backend built on PostgreSQL and TimescaleDB, you can seamlessly store Prometheus metrics and OpenTelemetry traces in TimescaleDB. This allows you to use SQL to analyze your observability data, getting unprecedented insights about your systems. Plus, can leverage features like compression, contintinuous aggregates, and data retention policies to automatically reduce your data volume and save storage costs, enjoy full compatibility with open source tools like Grafana and Jaeger, and the rock-solid reliability of PostgreSQL.

TransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner Music Group, Bosch, Uptake, Samsung, Northvolt, Siemens, Schneider Electric, Attentive, Zabbix, Ambient.ai, Embark, FlipsideCrypto, Nightfall, Charter Communications, and more.

With over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active Slack community, TimescaleDB is trusted by developers and teams around the world.

TimescaleDB is available as a self-hosted product under two licenses, the Timescale License (TSL) and the Apache 2 License. Both versions of TimescaleDB are completely free to use. For more information on Tiger Data’s licensing, click here.

For those looking to run TimescaleDB as a hosted product in the cloud, Tiger Data offers two options, Tiger Cloud and Managed Service for TimescaleDB. Tiger Cloud is a cloud platform owned and developed exclusively by Tiger Data, while Managed Service for TimescaleDB is operated by Tiger Data in partnership with Aiven.  For more information about Tiger Data’s hosted options and pricing, click here