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Prometheus is a service monitoring and time series database, which is open source.
Best Time Series Databases 2025
Time Series Databases (TSDB) are designed to store and analyze event data, time series, or time-stamped data, often streamed from IoT devices, and enables graphing, monitoring and analyzing changes over time.
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Learn More about Time Series Databases Software
What are Time Series Databases?
Time Series Databases are designed to collect and store data points that belong to a time series, meaning that the data is associated with timestamps. Time series data includes information that is collected continuously over time such as sensor readings, website data, stock prices, and other types of information collected over time. Time Series Databases are also equipped with specialized algorithms engineered to quickly query data to perform complex statistical analyses.
Time Series Databases and their analytical functionalities are used by companies for a variety of reasons. Many internet-based companies use Time Series Databases to capture behavioral data to produce user-specific advertisements. Such companies can also use these databases to monitor the health of their network and other associated systems. Companies that have physical machinery for which sensor data is constantly taken can also use these Time Series databases to predict when maintenance will be needed.
Time Series Databases Features
Most time series databases will include the following functionality:
- Built-in Data Analytics
- Real-time Insights
- BI Tool Integration
- Data Compression
- Security
- Data Manipulation
- Querying Language
- Data Retention Policies
- Graphic User Interface
- Data storage
Time Series Databases Comparison
When choosing a Time Series Database, prospective buyers will want to consider what type of data they will be storing. Some tools are optimized for large datasets that may come from IoT devices, but lack in their ability to store and analyze historical data. Timescale precision is another factor that will also help determine which tool is right.
Furthermore, Time Series Databases are optimized for storing and querying data that is associated with timestamps. Buyers should consider other kinds of databases (such as Relational Databases) if their data is not structured in this way.
Storage needs are another important consideration when choosing the right Time Series Database. Timestamped databases can often be quite large; therefore, one may need a tool that can easily downsample or compress the data to maintain enough storage capacity.
Pricing Information
Many Time Series Database providers offer a free version with limited features. For paid products, prospective buyers typically have two payment options. Buyers can choose a pay-as-you-go plan where the price is determined by the total amount of storage required, the query count, the number of writes, and that amount of transferred data. Flat-rate monthly payment plans geared toward larger enterprise use cases are also available.
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Time Series Databases FAQs
What do time series databases do?
Time Series Databases store continuously collected information that is associated with timestamps. This type of information is called time-series or historical data. Examples include website usage data, sensor readings, historical stock prices, etc. These tools also provide the means to query and analyze the data for myriad purposes.
What are the benefits of using time series databases?
The datasets collected and stored by Time Series Databases can often be very large (often measured in petabytes). These databases are specifically designed to handle large data sets and analyze them with great speed. Implementing a Time Series Database over a standard database can save an organization time and money, especially in terms of IT resources. Time Series Databases also provide strong analyses of the data, driving better business decisions.
What are the best time series databases products?
Some popular Time Series Databases are:
How much do time series databases cost?
Many open source offerings exist for Time Series Databases (such as Druid, InfluxDB, Prometheus, among others). For paid products, prospective buyers can expect to pay either based on the amount of data stored, queried, transferred, and written or based on a monthly flat rate.
