AWS Partners with InfluxData to Bring InfluxDB Open Source to Developers Around the World

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Today, AWS announced Amazon Timestream for InfluxDB, a new managed offering for AWS customers to run single-instance open source InfluxDB natively within the AWS console. This partnership represents a significant multi-year commitment by AWS to combine its global reach and accessibility with our industry-leading time series database, InfluxDB. AWS adding InfluxDB as a preferred time series database reflects the demand from AWS customers for InfluxDB and evidence of the time series market acceleration.

At InfluxData, we are deeply committed to open source–both building an open product that can be improved by InfluxData and the developer community and making this product accessible to as many developers as possible. This means simple, logical entry points and distributing InfluxDB to developers around the world.

To date, Timestream referred strictly to the time series database-as-a-service offered by Amazon. With the introduction of InfluxDB to the AWS product offering for time series, Amazon is also announcing the renaming of that database-as-a-service offering to “LiveAnalytics.” Moving forward, Timestream refers to the category of time series products offered by Amazon, which now includes LiveAnalytics and InfluxDB as distinct time series engines.

By partnering with AWS, we’re making open source InfluxDB available to developers in every industry, market, and region. In 2024, the cloud is the de facto platform for modern software. That also makes the cloud the best way to build, run, and distribute open source, so this partnership puts time series capabilities right in the hands of every developer working with AWS.

As developers increasingly rely on time series databases to manage IoT and real-time analytics workloads, our partnership with AWS becomes even more critical. Time series data is the foundation for highly intelligent, instrumented systems. Time series databases are key to collecting and managing data produced by these systems in real-time. AWS recognizes the rapid growth of this category and the need to give developers purpose-built tools to manage time series data with the lowest barrier to entry. Amazon Timestream for InfluxDB delivers on this vision.

Amazon Timestream for InfluxDB Now Available

Amazon Timestream for InfluxDB is a new way for developers to use a single-node open source InfluxDB on managed AWS infrastructure with the scalability, reliability, and security of the AWS ecosystem but without the overhead that comes with self-managing InfluxDB. With just a few clicks, you can quickly set up, migrate, operate, and scale an InfluxDB database on AWS. The managed instance automatically configures for optimal performance and availability so you can start building and running time series applications immediately. No upfront costs, licenses, or commitments are required, and you only pay for what you use.

Available today. The initial Amazon Timestream for InfluxDB offering is based on InfluxDB OSS 2.x, making it ideal for open source users with smaller workloads that only require a single-node instance. Through the console, customers can opt into additional performance and scalability. Today, this includes high availability with AWS Multi-AZ for synchronous data replication and backup across availability zones in as little as 60 seconds with zero data loss. It also includes AWS-grade security with encryption of data in transit and at rest with AWS Key Management Service (KMS) and a configurable network using Amazon Virtual Private Cloud (VPC).

Coming soon. Because we’re actively developing InfluxDB 3.0 open source, it isn’t yet available in Amazon Timestream for InfluxDB. The InfluxDB 3.0 product line will arrive in Timestream for InfluxDB in the form of InfluxDB Community, currently in development for the new product suite. Once available, we’ll deliver two new modules specific to the 3.0 product offering: a Scale Module for distributed querying from multiple instances and a Security Module for fine-grained permissions, single sign-on, and audit logging.

AWS-Hosted, InfluxData Managed, Powered by InfluxDB 3.0

Last year, we delivered a full product suite based on InfluxDB 3.0, our rebuilt database engine designed for time series analytics. InfluxDB 3.0 can ingest and analyze millions of data points per second, delivering real-time analytics for high-cardinality time series workloads. It also provides a 90 percent reduction in storage costs through best-in-category compression. With InfluxDB 3.0, users can perform advanced analytics on large fleets of devices in real-time at an unlimited scale. InfluxDB is an open platform based on the Open Data Architecture and built for seamless lakehouse integration.

Whether you need to manage small or enterprise-scale workloads, InfluxData and AWS have a product for you. InfluxDB Cloud Serverless runs on AWS and delivers a fully managed, elastic database running on multi-tenant cloud infrastructure. It’s ideal for teams with small to medium workloads. InfluxDB Cloud Dedicated also runs on AWS and provides users with dedicated, fully-managed cloud infrastructure optimized for large-scale workloads with added enterprise-grade security features. InfluxDB Cloud Dedicated and Serverless are part of the InfluxDB 3.0 product suite and include the latest capabilities for real-time analytics, support for SQL, and unlimited cardinality data, resulting in significant performance improvements.

Leading the Time Series Category

Time series databases are now foundational to the modern data stack. As the world around us becomes more instrumented, applications, sensors, and systems emit a relentless stream of time series data. This data, when collected and analyzed, delivers valuable real-time insights.

The partnership to make InfluxDB a preferred AWS time series database signifies InfluxData’s category leadership and the high-growth market for time series databases. Together with AWS, we will build on this momentum and drive the market forward with products that support developers at every stage of their time series journeys.