Edge Node Database Systems, the Internet of Things’ Hidden Workhorses

Are you creating software for a smart, connected device? One of the many “things” that make up the Internet of Things? McObject’s Webinar, “Edge Node Database Systems, the Internet of Things’ Hidden Workhorses” presents edge node DBMS requirements and a look at the field of available solutions. Topics covered include DBMS architectures, NoSQL, data complexity, off-the-shelf vs. roll-your-own data management approaches, and more.  Learn about IoT data management approaches and challenges for developers.

Learn more about eXtremeDB for edge node database systems.

eXtremeDB with Active Replication Fabric™ offers reliable data management for IoT by solving 5 challenges for IoT system developers:
• Bidirectional Replication
• Intermittent connections
• Multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud)
• Security
• Compression to maximize limited bandwidth networks

Resources:  IoT data management challenges and solutions

The Internet of Insurance Things, August 2, 2017 PropertyCausualty360.com by McObject CEO Steve Graves. How will the IoT affect the insurance industry with all the tools it can provide? Read more.

Industrial Internet of Things (IIoT) Database Usage in Rail Systems, insight.tech – February 1, 2017 As rail systems generate more data, developers need to rethink where and how they process information. Legacy systems moved data to the control center for analysis, but modern systems often keep this functionality on the train. Read more.

On the Challenges and Opportunities of IoT. Interview with Steve Graves, ODBMS Industry Watch – July 6, 2016

The IoT Technology Piece No One Is Talking About, Embedded Computing Design Guest Blog by McObject CEO Steve Graves

Enabling the IoT for Pre-IoT Infrastructure, Embedded Computing Design Guest Blog by McObject CEO Steve Graves

We have been testing, improving on, and retesting our software from the beginning in 2001 in order to provide our clients with the best possible data management solutions. Read “Database Persistence, Without The Performance Penalty” and more.

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Distributed Database Systems and Edge/Fog/Cloud Computing

A distributed database system is one in which the data belonging to a single logical database is distributed to two or more physical databases. Beyond that simple definition, there are a confusing number of possibilities for when, how, and why the data is distributed. Some are applicable to edge and/or fog computing, some others are applicable to fog and/or cloud  computing, and some are applicable across the entire spectrum of edge, fog and cloud computing.

Will the Real IMDS Please Stand Up?

In-memory database systems (IMDSs) have changed the software landscape, enabling “smarter” real-time applications and sparking mergers and acquisitions involving the largest technology companies. But IMDSs’ popularity has sparked a flurry of products falsely claiming to be in-memory database systems. Understanding the distinction is critical to determining the performance, cost and ultimately the success or failure of a solution. This white paper examines specific products, seeking to answer the question, “is it really an in-memory database system?”

Portability Techniques for Embedded Systems Data Management

For real-time embedded systems, database code portability means more than the ability to compile and execute on different platforms: portability strategies also tie into performance. Software developed for a specific OS, hardware platform and compiler often performs poorly when moved to a new environment, and optimizations to remedy this are very time-consuming. Truly portable embedded systems data management code carries its optimization with it, requiring the absolute minimum adaptation to deliver the best performance in new environments.