September 19, 2022 By Abhinav Srivastava 4 min read

Join SingleStore and IBM on September 21, 2022 for our webinar “Accelerating Real-Time IoT Analytics with IBM Cognos and SingleStore”.

Why real-time analytics matters for IoT systems

IoT systems access millions of devices that generate large amounts of streaming data. For some equipment, a single event may prove critical to understanding and responding to the health of the machine in real time, increasing the importance of accurate, reliable data. While real-time data remains important, storing and analyzing the historical data also creates opportunities to improve processes, decision-making and outcomes.

Smart grids, which include components like sensors and smart meters, produce a wealth of telemetry data that can be used for multiple purposes, including:

  • Identifying anomalies such as manufacturing defects or process deviations
  • Predictive maintenance on devices (such as meters and transformers)
  • Real-time operational dashboards
  • Inventory optimization (in retail)
  • Supply chain optimization (in manufacturing)

Considering solutions for real-time analytics on IoT data

One way to achieve real-time analytics is with a combination of a time-series database (InfluxDB or TimescaleDB) or a NoSQL database (MongoDB) + a data warehouse + a BI tool:

This architecture raises a question: Why would one use an operational database, and still need a data warehouse? Architects consider such a separation so they can choose a special-purpose database — such as a NoSQL database for document data — or a time-series database (key-value) for low costs and high performance.

However, this separation also creates a data bottleneck — data can’t be analyzed without moving it from an operational data store to the warehouse. Additionally, NoSQL databases are not great at analytics, especially when it comes to complex joins and real-time analytics.

Is there a better way? What if you could get all of the above with a general-purpose, high-performance SQL database? You’d need this type of database to support time-series data, streaming data ingestion, real–time analytics and perhaps even JSON documents.

Achieving a real-time architecture with SingleStoreDB + IBM Cognos

SingleStoreDB supports fast ingestion with Pipelines (native first class feature) and concurrent analytics for IoT data to enable real-time analytics. On top of SingleStoreDB, you can use IBM® Cognos® Business Intelligence to help you make sense of all of this data. The previously described architecture then simplifies into:

Real-time analytics with SingleStoreDB & IBM Cognos

 

Pipelines in SingleStoreDB allow you to continuously load data at blazing fast speeds. Millions of events can be ingested each second in parallel from data sources such as Kafka, cloud object storage or HDFS. This means you can stream in structured — as well as unstructured data — for real-time analytics.

But wait, it gets better…

  1. Once data is in SingleStoreDB, it can also be used for real-time machine learning, or to safely run application code imported into a sandbox with SingleStoreDB’s Code Engine Powered by Web Assembly (Wasm).
  2. With SingleStoreDB, you can also leverage geospatial data — for instance to factor site locations, or to visualize material moving through your supply chains.

Armis and Infiswift are just a couple of examples of how customers use SingleStoreDB for IoT applications:

  • Armis uses SingleStoreDB to help enterprises discover and secure IoT devices. Armis originally started with PostgreSQL, migrated to ElasticSearch for better search performance and considered Google Big Query before finally picking SingleStoreDB for its overall capabilities across relational, analytics and text search. The Armis Platform, of which SingleStoreDB now plays a significant part, collects an array of raw data (traffic, asset, user data and more) from various sources — then processes, analyzes, enriches and aggregates it.
  • Infiswift selected SingleStoreDB after evaluating several other databases. Their decision was driven in part because of SingleStore’s Universal Storage technology (a hybrid table type that works for both transactional and analytical workloads).

Want to learn more about achieving real-time analytics?

Join IBM and SingleStore on Sep 21, 2022 for our webinarAccelerating Real-Time IoT Analytics with IBM Cognos and SingleStore”. You will learn how real-time data can be leveraged to identify anomalies and create alarms by reading meter data, and classifying unusual spikes as warnings.

We will demonstrate:

  • Streaming data ingestion using SingleStoreDB Pipelines
  • Stored procedures in SingleStoreDB to classify data before it is persisted on disk or in memory
  • Dashboarding with Cognos

These capabilities enable companies to:

  • Provide better quality of service through quickly reacting to or predicting service interruptions due to equipment failures
  • Identify opportunities to increase production throughput as needed
  • Quickly and accurately invoice customers for their utilization

Register today!

Was this article helpful?
YesNo

More from Analytics

How the Recording Academy uses IBM watsonx to enhance the fan experience at the GRAMMYs®

3 min read - Through the GRAMMYs®, the Recording Academy® seeks to recognize excellence in the recording arts and sciences and ensure that music remains an indelible part of our culture. When the world’s top recording stars cross the red carpet at the 66th Annual GRAMMY Awards, IBM will be there once again. This year, the business challenge facing the GRAMMYs paralleled those of other iconic cultural sports and entertainment events: in today’s highly fragmented media landscape, creating cultural impact means driving captivating content…

How data stores and governance impact your AI initiatives

6 min read - Organizations with a firm grasp on how, where, and when to use artificial intelligence (AI) can take advantage of any number of AI-based capabilities such as: Content generation Task automation Code creation Large-scale classification Summarization of dense and/or complex documents Information extraction IT security optimization Be it healthcare, hospitality, finance, or manufacturing, the beneficial use cases of AI are virtually limitless in every industry. But the implementation of AI is only one piece of the puzzle. The tasks behind efficient,…

IBM and ESPN use AI models built with watsonx to transform fantasy football data into insight

4 min read - If you play fantasy football, you are no stranger to data-driven decision-making. Every week during football season, an estimated 60 million Americans pore over player statistics, point projections and trade proposals, looking for those elusive insights to guide their roster decisions and lead them to victory. But numbers only tell half the story. For the past seven years, ESPN has worked closely with IBM to help tell the whole tale. And this year, ESPN Fantasy Football is using AI models…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters