Time series is a series of time-value pairs in a successive, timely order. As an example, a daily/or a monthly closing price over a year.
It is commonly used for storing, searching, retrieving, and managing timely data.
Time series has 4 components which are:
Secular trend: describes the movement along the term
Seasonal variation (changes) over the time
Cyclical fluctuations: represent the periodical changes but not corresponding with the seasonal variation
Irregular variations
Time series are used in statistics, finance (accounting), data analytics, mathematics, artificial intelligence, pattern recognition, medicine, communication engineering, security analytics, and many other domains.
What is TimescaleDB?
TimescaleDB is an open-source project that supercharges PostgreSQL with time series management tools, to speed up the data processing and provide faster queries than its parent (PostgreSQL) or its other counterparts.
It comes with two editions, a community edition that is fully open-source and hosted (managed) edition which features more tools, and options.
TimescaleDB Features
Significantly fast, 10-100x time than PostgreSQL, MongoDB, InfluxDB.
Supports relational time-series
Works on big data: tested on millions of records per node
Runs on Amazon Web Services (AWS), Microsoft Azure, IBM cloud
Developer-friendly API: If you are familiar with PostgreSQL, you can dive directly into Timescale
Self-hosted and on-premise
Support complex queries
Works as PostgreSQL
Multi-platform support: Linux (Ubuntu, RedHat Linux, CentOS, and Debian), macOS, and Windows.
Docker installation support
Third-party tools
Developer-friendly docs
License
TimescaleDB is released under Apache license 2.0, and Timescale License.
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