In today's data-driven landscape, time series data has become a valuable resource for businesses, driving critical applications and offering valuable insights.
Choosing the best time series database for each use case is essential, as analyzing time-series data efficiently represents some important challenges. However, given the wide range of options available, making an informed decision can become difficult. So where should you start and what are the most important aspects to consider when selecting the best database for time series data? We give you some key aspects to consider.
Key Criteria for Choosing the best time-series database
- Performance and Scalability: It is important to choose the fastest time series database that can efficiently handle the ingestion, storage, and retrieval of time series data, even as the data volumes continue to grow. Scalability is equally important, as it ensures that your database can seamlessly expand to accommodate the increasing data loads as your business evolves, ensuring that it can scale vertically and horizontally.
- Query language: Choose a database that offers a powerful query language, capable of handling intricate operations, time-based filtering, and aggregations. A query language that is intuitive and expressive enhances the efficiency and accessibility of data analysis. SQL is a popular query language that is widely used and known for its simplicity, making it a user-friendly option for performing data analysis tasks. In the market, there are several time-series databases with their own proprietary or custom language and this can discourage many developers from using them.
- Data Model and Schema: Analyze the database's data model and schema flexibility to ensure it aligns seamlessly with your data structure and use case. Certain databases provide the advantage of schema-less flexibility, while others follow a more structured approach. Selecting a model that perfectly suits your specific data organization requirements is important. Considering also a versatile time-series database that can adjust to your future needs (not just time-series) is essential to keep your total cost of ownership down.
- Security and Maintainability: Data security and maintainability are non-negotiable. Look for a database that provides reliable and robust security features, including encryption, authentication, and authorization. It also needs to reduce the burden on your team, ensuring data integrity and availability, so it is crucial to consider the time and resources required for long-term maintenance, including managing backups, replicas, data retention, archiving, automation, and more.
- Reliability: To minimize downtime, your time series database should be highly available with data replication, backup, and failover mechanisms. A reliable database ensures your critical time series data is accessible when you need it, without interruptions or data loss.
Comparing all the options to find the best time-series database
Begin by clearly defining your business's specific needs, objectives and technical aspects. Take into consideration important aspects like the volume of data, the speed at which data is generated, the complexity of queries, the ability to scale, and how well the chosen database integrates with your existing tools and systems.
With some research and analysis, identify the top time series- databases that align with your needs. Some popular options are InfluxDB, TimescaleDB, CrateDB, and others. Assess them based on the key criteria listed in the previous section.
Next, you can establish benchmarks and conduct performance tests using sample data that resembles your use case. Measure and analyze query response times, write speeds, and the scalability of the databases under consideration. Lastly, performing a cost analysis to determine the financial implications of each potential candidate. For that, considering an open-source time-series database is very helpful.
CrateDB: The Time Series Database that Truly Scales
CrateDB is widely recognized as one of the leading time-series databases, offering unparalleled capabilities to process very large data workloads with hyper-fast speed, thanks to its distributed architecture.
Offering native SQL, it seamlessly integrates with other systems, making it a popular choice for businesses of all sizes to manage time-series data. With high scalability and built-in availability, CrateDB allows to handle the demands of an ever-growing dataset with unbounded cardinality.
Thanks to its flexible data model, CrateDB can also address other types of projects (SQL, NoSQL, full-text, vector-search, BLOB), limiting the need for multiple different types of databases.
CrateDB support allows businesses to tailor their database structures to meet specific requirements, and the deployment process is a simple and straightforward experience according to the users, while seamlessly processing millions of data points per second.