Watch the on-demand Webinar
IoT: Implications on Database Management
“Run length encoding can reduce data storage requirements by up to 90% and increase analytics speed up to 21%.”
“Local processing can reduce the data transport and upstream storage requirements by up to 99%.”
What we covered
What used to be “embedded systems” are now more popularly known as IoT edge devices and gateways. And, while they may retain many of the same characteristics of embedded systems of times past, there are also differences. This presentation explored those old and new characteristics and their implications on DBMSs. Our goal is to equip developers with knowledge they will need when considering database system alternatives.
- Where the edge is depends on who you ask
- Old verses new characteristics of IoT DBMS requirements
o Time series data
o Machine Learning
We explored what works and pitfalls to avoid, and invited project specific questions after the presentation.
We invite you to review additional research, and learn more about eXtremeDB
We are a dedicated group of specialists and our only focus is database management systems. See our Related Resources below for our other IoT database Webinars, journal articles and white papers about embedded database management.
Webinars for Professional Developers
Watch to on-demand Webinars, hosted by experts, about proven database management system practices. Watch “Eliminating Database Corruption“. Or, “Embedded Databases: Make or Break Technology Choices for High Performance Applications” and others.
Review our list of Webinars
Articles for Professional Developers
- Change Data Capture in Embedded Databases Embedded Computing Design
- Industrial Internet of Things (IIoT) Database Usage in Rail Systems insight.tech
- The Importance of Distributed Databases for the Internet of Things Embedded Software Engineer – ESE Kongress edition, page translates
See a list of articles
White Papers for Professional Developers
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.
Review our research
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.
White paper: Will the Real IMDS Please Stand Up?
In-memory database systems (IMDSs) have changed the software landscape, enabling “smarter” embedded 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?”