Solving one of PostgreSQL's biggest weaknesses.
Dreams of Codeγ»2 minutes read
Postgres is popular for relational data but has limitations with Big Data, particularly time series data exceeding 50 gigabytes. Timescale DB, an extension of Postgres, offers speed and scalability for time series data through partitioning and continuous aggregations, significantly reducing query times from minutes to milliseconds.
Insights
- Postgres is a widely used database for relational data, but it struggles with Big Data exceeding 50 gigabytes due to limitations.
- Timescale DB, an extension of Postgres, specializes in time series data like stock prices, offering speed and scalability by partitioning data into hyper tables and providing continuous aggregations for significant performance enhancements.
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Recent questions
What is Postgres known for?
Relational data storage with SQL language.
What are the limitations of Postgres?
Handling Big Data exceeding 50 gigabytes.
What is time series data?
Data indexed in time order, like stock prices.
What is Timescale DB?
Extension of Postgres for time series data.
How can Timescale DB optimize query speeds?
Through continuous aggregations and data refresh policies.
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