InfluxData, the company behind the top time series database InfluxDB, has made InfluxDB 3 Core and InfluxDB 3 Enterprise available on Amazon Timestream for InfluxDB. This is the first time InfluxDB 3 is available as a managed service on Amazon Web Services (AWS), giving developers access to a next-generation time series database without the burden of infrastructure management.
InfluxDB 3 Core is an open-source engine. It excels in real-time use cases. InfluxDB 3 Enterprise offers high availability, better security, and improved performance. It’s designed for production use and can scale as needed. Both are now available in 14 AWS regions. This makes it easier for developers to handle millions of high-resolution data streams in real time. You can easily connect the streams with AWS services like Lambda, SageMaker, and Kinesis. This helps speed up AI/ML pipelines and real-time decision-making.”Real-time isn’t a feature. It’s the underpinning of all smart, autonomous systems,” stated Evan Kaplan, InfluxData CEO. “Time series fuels AI, anomaly detection, and predictive analytics through constant input to the models that inform real-time decisions. With InfluxDB 3 on AWS, developers have the infrastructure to respond instantly, transforming high-volume streams of data to insight and action in real-time.”
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The customers’ capability to develop real-time AI/ML applications and autonomous systems at huge scale is really exciting,” stated Brad Bebee, Director, AWS Timestream. “With our integration with InfluxData, customers can now use AWS to run InfluxDB 3, offloading the management of infrastructure, allowing them to focus on crafting insights from their time series data streams.
InfluxDB 3 Enterprise on Amazon Timestream for InfluxDB is a robust engine for scale time series data management that streamlines operations and minimizes infrastructure overhead. It is designed for production use from day one with enterprise features such as multi-region durability, read replicas, automatic failover, and more robust security. Its diskless, cloud-native design makes operations easier with automatic scalability and low-latency performance, supporting the most demanding time series workloads.
Both Enterprise and Core editions feature a built-in Processing Engine, a Python virtual machine that enables developers to execute custom logic on incoming data, transforming, enriching, monitoring, and alerting data without third-party services or pipelines. From prediction to anomaly detection and failure insight, the Processing Engine processes and responds to streaming data in real time, within the database.
“Through scaling our application and infrastructure, we required a managed, scalable time series database with real-time analytics ability while monitoring a broad set of metrics,” said KreditBee CTO Karthikeyan Krishnaswamy. “Timestream for InfluxDB was the perfect fit, providing cost-effective, high-speed monitoring without worrying about cost per metric or data point.”