InfluxData this week made generally available updates to the open source and commercial versions of its time-series database that in addition to improving performance can now be deployed in minutes.
InfluxDB 3 Core is an open source time-series database that is widely used to drive a range of event-driven applications. The InfluxDB 3 Enterprise commercial version of the database adds high availability, enhanced security, and an ability to be deployed across multiple cloud regions to increase scalability.
InfluxData CEO Evan Kaplan said rather than trying to provide support services to the open source edition of the database, InfluxDB opted to provide a separate edition that provides enterprise IT organizations with capabilities that are now available in the open source version. That approach enables InfluxData to generate revenue without having to resort to applying more restrictive licensing terms on the core open source edition of the database that is today made available under a permissive MIT/Apache 2 license, noted Kaplan.
That’s critical because it eliminates any incentive there might be to fork the underlying InfluxDB 3 Core codebase in a way that has occurred multiple times across other open source projects that have been launched by other IT vendors, he noted.
At the core of InfluxDB is a processing engine based on a columnar database that allows developers to transform, enrich, monitor and generate alerts on streaming data. It is designed to ingest millions of writes per second to capture high-resolution time series data without lags in a way that doesn’t require IT teams to set up extract, transform and load (ETL) pipelines.
Additionally, analysts can use SQL to query data with sub-10ms lookups across datasets that have unlimited cardinality, noted Kaplan.
InfluxData provides both an edition of its database that is managed in the cloud as a service, and can be deployed as an on-premises edition by an IT team on Kubernetes clusters. Both editions are based on version 3.0 of InfluxDB that is now based on a columnar engine, dubbed IOx, that leverages the open source Apache Arrow memory format. The database itself is written in the Rust programming language.
That foundation makes it possible to continuously ingest, transform and analyze hundreds of millions of time series data points per second. At the same time, InfluxDB takes advantage of high compression object storage to reduce the total cost of storing all that data. It also provides interoperability with Open Data Architecture (ODA) to integrate with data lakes based on open source platforms such as DataFusion, Flight SQL and Parquet that are being advanced by the Apache Software Foundation (ASF).
It’s not clear how widely time-series databases are now being employed, but as more event-driven applications are used to drive, for example, internet of things (IoT) applications, the number of use cases continue to expand. The challenge, however, is finding and retaining the expertise needed to manage time-series databases that typically require higher levels of data engineering expertise to successfully manage at scale.
