InfluxData’s Time Series Database adds data replication to unify edge and cloud environments

Time-series database company InfluxData Inc. today announced the addition of 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 provides developers with a way to collect, store, and also analyze high-precision time series data in InfluxDB at the network edge, while simultaneously replicating data across the cloud.

InfluxData is the company behind InfluxDB, a time series database designed to manage time-processed information. For example, heat readings from an industrial temperature sensor should be organized in the exact order they were created, with an accurate timestamp, so users can track changes in heat in a machine over time. . This type of context is also needed for various other applications, such as performance monitoring.

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

Today’s update extends these capabilities to the edge of distributed networks. InfluxData explains that many companies operate distributed applications that generate massive volumes of time series data. Some may rely on thousands of “Internet of Things” sensors installed on equipment across multiple factories, for example. But these companies lack an efficient way to manage the data generated by these sensors, and they lack the ability to create and manage hundreds or even thousands of data pipelines.

With InfluxDB’s Edge Data Replication feature, that’s no longer an issue. It enables a new Edge database setup that can collect and organize time-series data from distributed assets, analyze that information on-premises, and then replicate it all to a centralized version of InfluxDB that runs 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 great benefits to businesses, InfluxData said. He explained that companies are increasingly deploying artificial intelligence and machine learning models at the edge to process data on-premises, rather than migrating it to the cloud in the first place. By doing so, it is possible to gain insights from edge-generated data faster and to act faster.

InfluxData said the benefits of processing data at the edge include lower cloud ingress and egress costs. Users will be able to intelligently filter and aggregate data from InfluxDB at the edge before replicating it into InfluxDB Cloud, enabling faster processing and lower data transfer costs. Data can also be transformed at the edge, with added context to allow it to be processed more efficiently in the cloud, the company said. Additionally, Edge Data Replication provides a buffer against connectivity interruptions, queuing data at the edge until it can be transferred to the cloud.

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

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


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