Why You Need a Real-Time Data Warehouse for IoT Applications

Mike Boyarski
Mike Boyarski

As always-on devices and sensors proliferate, the data emitted from these devices provides meaningful insights to improve customer experiences, optimize costs, and identify new revenue opportunities. In a recent report, Taking the Pulse of Enterprise IoT from McKinsey & Company, 48 percent of respondents cited “managing data” as a critical capability gap related to their IoT initiatives.1

The data infrastructure behind IoT applications requires a high performing and easy-to-access platform to support immediate responses to changing conditions. At the center of an IoT data infrastructure platform there needs to be a database that supports stream data ingestion with familiar SQL query access on a scalable, highly available platform.

MemSQL powers a number of IoT applications to help manage operating costs while improving the customer experience. These applications require core database capabilities including:

Streaming data ingest and store

The database must collect and store multiple streams of data into relational formats to support real-time and historical analysis. Ingestion often requires inserts, updates, and deletes to ensure data accuracy.

Fast query response

Perform instant queries across millions of events or devices to discover real-time anomalies or predict events leveraging historical data using memory-optimized SQL.

Proven compatibility

Leverage the familiarity of ANSI SQL with full data persistence to drive sophisticated analytics while seamlessly working with existing business intelligence and middleware tools.

Scalability and availability

Utilize a modern shared nothing architecture to scale out with industry-standard hardware. Built-in resilience keeps the database online across cloud or on-premises deployments.

MemSQL has been able to help industry-leading organizations such as Uber, Verizon, Comcast, and Cisco deliver IoT applications powered by analytics at scale. These applications include:

Real-Time monitoring and detection, which can be used to manage networks and devices with instant insights to live conditions to improve customer experience while mitigating costs.

Predictive maintenance applications, which can identify potential issues before they arise to prevent outages or improve asset management for oil pumps, wind farms, vehicles, and more.

Fleet optimization, which can help optimize cost by identifying the location and condition of every truck or car to streamline delivery or improve customer satisfaction.

Learn more about the real-time analytic solutions for IoT applications by downloading our new IoT Analytic Solution Guide.

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1 Taking the pulse of enterprise IoT, July 2017

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