Hi, I'm the author. There are a few things worth noting:
1. Time-series data (data collected over time, e.g., DevOps data, financial data, sensor data) is a growing (and lately, quite popular) type of "big data" thanks to a number of trends: more sources of data, cheaper storage, rise of a monitoring culture, IoT, etc.
2. One of the characteristics of time-series data is that it grows very, very quickly (e.g., when collecting data every few seconds), making it hard to use traditional relational databases for storage. In response, people have developed specialized time-series databases, which so far achieve scalability by sacrificing query power.
3. We just released a new time-series database that takes a different approach, achieving both scalability and query power. One of the benefits of our approach is that one can use normal SQL to run queries, something that was missing in prior time-series databases. Another benefit is that we are tightly integrated with PostgreSQL, one of the most popular, reliable, stalwarts of the database world. A lot of people find this approach useful.
If you collect any type of time-series data, then I welcome you to take a closer look. Happy to answer any other questions.
1. Time-series data (data collected over time, e.g., DevOps data, financial data, sensor data) is a growing (and lately, quite popular) type of "big data" thanks to a number of trends: more sources of data, cheaper storage, rise of a monitoring culture, IoT, etc.
2. One of the characteristics of time-series data is that it grows very, very quickly (e.g., when collecting data every few seconds), making it hard to use traditional relational databases for storage. In response, people have developed specialized time-series databases, which so far achieve scalability by sacrificing query power.
3. We just released a new time-series database that takes a different approach, achieving both scalability and query power. One of the benefits of our approach is that one can use normal SQL to run queries, something that was missing in prior time-series databases. Another benefit is that we are tightly integrated with PostgreSQL, one of the most popular, reliable, stalwarts of the database world. A lot of people find this approach useful.
If you collect any type of time-series data, then I welcome you to take a closer look. Happy to answer any other questions.