![Guide to Postgres Data Management](/blog/content/images/size/w300/2023/10/Screenshot-2023-10-20-at-9.07.59-AM.png)
![Guide to Postgres Data Management](/blog/content/images/size/w300/2023/10/Screenshot-2023-10-20-at-9.07.59-AM.png)
![Time-Series Data: What It Is, and How to Use It](/blog/content/images/size/w300/2018/12/timeseries.png)
![Time-Series Analysis: Function Examples](/blog/content/images/size/w300/2023/04/time-series-analysis-function-examples.jpg)
![PostgreSQL + TimescaleDB: 1,000x Faster Queries, 90 % Data Compression, and Much More](/blog/content/images/size/w300/2023/10/Screenshot-2023-10-11-at-7.24.23-PM.png)
PostgreSQL + TimescaleDB: 1,000x Faster Queries, 90 % Data Compression, and Much More
TimescaleDB expands PostgreSQL query performance by 1,000x, reduces storage utilization by 90%, and provides time-saving features for time-series and analytical applications—while still being 100% Postgres.
![Timescale Tips: Testing Your Chunk Size](/blog/content/images/size/w300/2022/08/TimescaleCloud_Tips_Blog_Hero--1--2.png)
![State of PostgreSQL 2022—13 Tools That Aren't psql](/blog/content/images/size/w300/2022/07/Blog-Hero.png)
State of PostgreSQL 2022—13 Tools That Aren't psql
Performance and tooling are frequently debated in the State of PostgreSQL survey, and this year was no exception. With psql remaining the number one tool for querying and admin among PostgreSQL users, we decided to compile a list of tools— that aren’t psql—to broaden your options.
![State of PostgreSQL: How to Contribute to PostgreSQL and the Community](/blog/content/images/size/w300/2022/07/Blog-Hero--2---1-.png)
State of PostgreSQL: How to Contribute to PostgreSQL and the Community
Community contribution remains a recurrent theme in the State of PostgreSQL survey. As we prepare to release the full report later this month, we dig into some of the results and leave you tips on how to contribute to PostgreSQL and its community.
![State of PostgreSQL 2022—First Findings](/blog/content/images/size/w300/2022/07/BlogHero_First-Findings.png)
![How We Made Data Aggregation Better and Faster on PostgreSQL With TimescaleDB 2.7](/blog/content/images/size/w300/2022/06/candlesticks-2.png)
How We Made Data Aggregation Better and Faster on PostgreSQL With TimescaleDB 2.7
They’re so fast we can’t catch up! Check out our benchmarks with two datasets to learn how we used continuous aggregates to make queries up to 44,000x faster, while requiring 60 % less storage (on average).
![Point-in-Time PostgreSQL Database and Query Monitoring With pg_stat_statements](/blog/content/images/size/w300/2022/05/PIT-PostgreSQL-Database-Query-Monitoring--1-.png)
![Teaching Elephants to Fish](/blog/content/images/size/w300/2022/04/PostgreSQL-community-elephants.jpg)
![Using pg_stat_statements to Optimize Queries](/blog/content/images/size/w300/2022/03/pg-stat-statements-timescale-2.png)
![Select the Most Recent Record (of Many Items) With PostgreSQL](/blog/content/images/size/w300/2023/10/Screenshot-2023-10-11-at-6.56.02-PM.png)
![How to shape sample data with PostgreSQL generate_series() and SQL](/blog/content/images/size/w300/2022/01/pexels-burak-kebapci-187041.jpg)
![Generating More Realistic Sample Time-Series Data With PostgreSQL generate_series()](/blog/content/images/size/w300/2021/11/pierre-chatel-innocenti-F4VHOj76D0o-unsplash.jpg)
![What Is ClickHouse and How Does It Compare to PostgreSQL and TimescaleDB for Time Series?](/blog/content/images/size/w300/2023/09/Timescale-vs-clickhouse-hero.png)
![How to Create (Lots!) of Sample Time-Series Data With PostgreSQL generate_series()](/blog/content/images/size/w300/2023/10/Screenshot-2023-10-12-at-5.55.04-PM.png)
How to Create (Lots!) of Sample Time-Series Data With PostgreSQL generate_series()
Generating sample time-series data with the PostgreSQL generate_series() function is a useful skill to have when evaluating new database features, creating demonstrations, or testing insert and query patterns. Learn what PostgreSQL `generate_series()` is and how to use it for basic data generation.
![Hacking NFL data with PostgreSQL, TimescaleDB, and SQL](/blog/content/images/size/w300/2021/07/ameer-basheer-Yzef5dRpwWg-unsplash--1-.jpg)
Hacking NFL data with PostgreSQL, TimescaleDB, and SQL
Learn how to use time-series data provided by the NFL to uncover valuable insights into many player performance metrics – and ways to apply the same methods to improve your fantasy league team, or your knowledge of the game - all with PostgreSQL, SQL, and freely available extensions.
![2021 State of PostgreSQL survey results](/blog/content/images/size/w300/2021/05/Social-Cover--optional-.png)
2021 State of PostgreSQL survey results
Postgres is one of the most popular and loved databases in the world, even after 30+ years of development. Learn how developers use Postgres today, from the use cases they’re tackling and places they go to share and learn to opportunities for improvement in the Postgres community, and more.
![Improving DISTINCT Query Performance Up to 8,000x on PostgreSQL](/blog/content/images/size/w300/2021/05/pexels-pixabay-373543.jpg)
![TimescaleDB vs. Amazon Timestream: 6,000x Higher Inserts, 5-175x Faster Queries, 150-220x Cheaper](/blog/content/images/size/w300/2023/08/timescale-vs-amazon-timestream-2023-08-02---Timestream---Compare---Hero.png)
TimescaleDB vs. Amazon Timestream: 6,000x Higher Inserts, 5-175x Faster Queries, 150-220x Cheaper
Our TimescaleDB vs Amazon Timestream results surprised us, but even after testing several configurations, we found Timestream slow, expensive, and missing key database capabilities like backups, restores, updates, and deletes.