Time-series database company InfluxData Inc. said today it’s adding a new feature called Edge Data Replication that enables more centralized business intelligence from widely distributed computing environments.

The Edge Data Replication feature is available starting today and gives developers a way to collect, store and also analyze high-precision time series data within InfluxDB at the network edge, while simultaneously replicating the data in the cloud.

InfluxData is the company behind InfluxDB, a time-series database designed to handle information that’s processed chronologically. For instance, heat readings from an industrial temperature sensor must be arranged in the exact order they’re created, with a precise timestamp, so users can track how the heat in a machine fluctuates over time. That kind of context is also necessary for various other applications, such as performance monitoring.

InfluxDB provides the foundation for storing and analyzing such data. Notably, the database is simple to deploy and provides high performance, with the ability to perform millions of data operations per second, the company claims.

Today’s update expands those capabilities to the edge of distributed networks. InfluxData explains that many companies operate distributed applications that generate massive volumes of time-series data. Some might rely on thousands of “internet of things” sensors fitted to equipment across multiple factories, for example. But these companies lack an effective way to manage the data generated by those sensors, and they don’t have the capability to create and manage hundreds or even thousands of data pipelines.

With InfluxDB’s Edge Data Replication feature, that’s no longer a problem. It enables a new edge database configuration that can collect and organize chronological data from distributed assets, analyze this information onsite, and then replicate everything in a centralized version of InfluxDB that’s running in the cloud. According to the company, it provides a simple solution to the challenge of integrating and orchestrating hundreds of data streams from distributed applications.

The ability to process time-series data at the edge brings big benefits to enterprises, InfluxData said. It explained that companies are increasingly deploying artificial intelligence and machine learning models at the edge to process data on site, rather than migrating it to the cloud first of all. By doing so, it’s possible to derive insights from edge-generated data faster and act on them more quickly.

InfluxData said the advantages of processing data at the edge include reducing cloud ingress and egress costs. Users will be able to filter and aggregate data intelligently from InfluxDB at the edge before replicating it within InfluxDB Cloud, enabling faster processing and reduced data transfer costs. Data can also be transformed at the edge, with context added to enable it to be processed in the cloud more effectively, the company said. Further, Edge Data Replication provides a buffer against connectivity disruption, queuing data at the edge until such time as it can be transferred to the cloud.

InfluxData Vice President of Products Rick Spencer said that most data today is born at the edge of the network. Unfortunately, he said, existing databases don’t respect these “emerging hybrid edge-cloud environments.”

“Edge Data Replication sets a new benchmark for time series platforms by combining the power of cloud with the precision of the edge – a best-of-both-worlds solution that’s key to tomorrow’s distributed applications,” he said.

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