New capabilities combine the power of cloud with the precision of the IoT edge to optimize time series data processing
InfluxData, creator of the leading time series platform InfluxDB, announced Edge Data Replication, a new capability for centralized business insights in widely distributed environments. Edge Data Replication enables developers to collect, store and analyze high-precision time series data in InfluxDB at the edge, while replicating all or subsets of this data into InfluxDB Cloud. With Edge Data Replication, InfluxData delivers on both platform breadth and simplicity, scaling time series data processing in a new way that embraces the precision of the edge and the power of the cloud.
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“Data has gravity, and much of it is created far from clouds and data centers. This pulls applications out to the edge, where the data is born and produces its greatest value. Unfortunately, most databases don’t acknowledge or respect these emerging hybrid edge-cloud environments”
Modern applications are highly distributed across architectures and produce enormous volumes of time series data at the edge. Effectively managing the data in these applications and associated assets is a time-consuming, resource-intensive process, and developers often don’t have the capabilities or budgets to manage hundreds or thousands of data pipelines. InfluxDB Edge Data Replication changes the way developers and operators process time series data across distributed environments using a new edge database configuration that durably queues and mirrors select datasets to the cloud. The availability of Edge Data Replication marks a critical first step in InfluxData’s journey to solve key time series data integration and orchestration challenges for customers building distributed Industrial and Internet of Things (IoT) applications in energy, manufacturing, aerospace, and other high-tech industries.
“Data has gravity, and much of it is created far from clouds and data centers. This pulls applications out to the edge, where the data is born and produces its greatest value. Unfortunately, most databases don’t acknowledge or respect these emerging hybrid edge-cloud environments,” said Rick Spencer, Vice President of Products, InfluxData. “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.”
According to Gartner®, “Enterprises are now employing machine learning models and computing at the edge in order to preprocess data rather than just migrating data to the cloud. Rather than one-way archiving, early adopters are doing multidirectional synchronization of data between edge, core data center and public cloud. Two-way synchronization allows enterprises to make use of the elastic nature of the compute infrastructure found among cloud service providers. Furthermore, with the upcoming expansion of edge computing, there will be a growing need for solutions that enable data workflow among edge, storage and multiple public cloud providers.”*
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Unlock Centralized Business Insights with Edge Data Replication
InfluxData’s Edge Data Replication creates a new and intuitive experience for developers building at the edge by allowing data from an InfluxDB instance to automatically replicate to InfluxDB Cloud with a simple configuration setting. By leveraging Edge Data Replication in tandem with the full power of the InfluxDB platform, including Flux, InfluxDB’s native data scripting language, users can:
- Integrate edge and cloud DataOps: Connect edge and cloud workloads to automatically mirror data from InfluxDB edge sources to InfluxDB Cloud instances in real-time.
- Reduce cloud ingress and egress costs: Filter and aggregate data intelligently from InfluxDB at the edge before replicating it to InfluxDB Cloud. Downsampling data with Edge Data Replication delivers faster processing and reduced transfer costs.
- Transform data before transfer: Dynamically add context to edge data that is needed for processing in the cloud. Cloud processing may require extra dimensions to query on or feature engineering.
- Enforce edge/cloud consistency: Withstand planned and unplanned disruptions in network connectivity by queueing data at the edge until it can be safely transferred to the cloud.
- Full data workflow at the edge: Full support for applications at the edge by enabling data preprocessing close to the data sources.
“Loft Orbital’s mission is to deliver space infrastructure as a service to give our customers rapid access to space,” said Caleb MacLachlan, Head of Software Integration, Loft Orbital. “Our network edge extends onto our spacecraft in low Earth orbit, requiring real-time access to highly distributed mission-critical data. With Edge Data Replication, it’s easier than ever for us to centralize our time series data while ensuring we don’t lose data from edge storage locations.”
“Every year there are 10 times more IoT edge devices deployed. Developers know that expectations for consistency, efficiency, and reliability are growing at a similar rate,” said Rick Spencer, InfluxData. “With this kind of scale, IoT developers need excellence in local operations, taking advantage of granular data for real-time insights and control, while also having a centralized view across all of the edge operations, sometimes at an enormous scale. The combination of Edge Data Replication, InfluxDB at the edge, and InfluxDB Cloud makes building such IoT applications not only possible, but also incredibly simple.”
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