Watch the on-demand Webinar
Webinar: What Makes a Database System ‘In-memory’?
In-memory database systems (IMDSs) are held out as the ideal database solution for embedded systems software. But what is unique about IMDSs versus caching, RAM-disks, “memory tables”, and solid-state disks? In fact, the differences are significant, and can be critical to your embedded software projects. Join McObject CEO Steve Graves to explore this topic, including the limitations (and burden) of database caching; data transfer and duplication; volatility and recoverability, and more. Gain ideas and techniques for building better, faster software.
It’s in-memory foundation is one way eXtremeDB reduces memory usage in embedded systems. Review the other memory-saving features.
For more information about in-memory database performance, review a summary of the white paper, Gaining an Extreme Performance Advantage.
Not all in-memory database management systems are created equal. Learn why in the summary of the white paper: Will the Real In-memory Database Please Stand Up?
What makes eXtremeDB different?
Our extensive combination of features. Learn about features designed to:
Related Resources

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
Fault-Tolerant Memory Management for Mission Critical Embedded Systems
Memory management is a key programming concept for eliminating the possibility of bottlenecks and failure in embedded software. This Webinar presents memory management techniques to optimize code, focusing on the beneficial role of highly efficient custom allocators. The solutions presented retain the power and flexibility of dynamic memory management while mitigating common risks, and improving efficiency and performance.
Using Data Indexes to Boost Performance and Minimize Footprint in Embedded Software
The right index can boost lookup speed logarithmically, and reduce RAM and CPU demands. While the B-Tree is the best known index, many others can be more efficient in specific circumstances, such as geospatial/mapping and telecom/networking applications. This Webinar examines less well-known indexes including T-Tree, Hash table, R-Tree, Patricia trie and others. It emphasizes index implementation methods that avoid data duplication, to minimize an memory footprint.

Articles for Professional Developers
Review a list of articles
- 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

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
White paper: Exploring Code Size and Footprint
The terms ‘code size’ and ‘footprint’ are often used interchangeably. But they are not the same; code size is a subset of footprint. This paper will explain the differentiation and relevance, then proceed to describe some of the techniques employed within eXtremeDB to minimize footprint.
White paper: In-Memory Database Systems: Myths and Facts
In the past decade, software vendors have emerged to offer in-memory database system (IMDSs), described as accelerating data management by holding all records in main memory. But is this new? For years, database management systems have employed caching. Several vendors offer something called “memory tables.” RAM-disks and — more recently — Flash-based solid state drives (SSDs) are available for use with databases. Do IMDSs really add anything unique? In fact, the distinction between these technologies and true in-memory database systems is significant, and can be critical to project success. This paper explains the key differences, replacing IMDS myths with facts.
White paper: Will the Real IMDS Please Stand Up?
In-memory database systems (IMDSs) have changed the software landscape, enabling “smarter” and faster 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?”
White paper: Portability Techniques for Embedded Systems
Whether an embedded systems database is developed for a specific application or as a commercial product, portability matters. Most embedded data management code is still “homegrown,” and when external forces drive an operating system or hardware change, data management code portability saves significant development time. This is especially important since increasingly, hardware’s lifespan is shorter than firmware’s. For database vendors, compatibility with the dozens of hardware designs, operating systems and compilers used in embedded systems provides a major marketing advantage.

Originally designed as an in-memory database system.
Learn why this matters.
Embedded & Real-time Systems
The eXtremeDB in-memory database system was designed specifically for use in resource-constrained, mission-critical and safety-critical embedded systems.
Learn more about eXtremeDB in-memory database for embedded systems
Learn what makes eXtremeDB ideal in real-time systems
High Performance Computing
eXtremeDB in-database analytics offers breakthrough efficiency and can be used with the product’s in-memory database system (IMDS) capability, or independent of it.
Learn about hybrid eXtremeDB for Big Data and Analytics or for Financial systems
Learn more about the IMDS as a powerful, persistent memory caching solution.
Hybrid In-memory and/or Persistent
Combine both database paradigms – in-memory and on-disk – in a single database instance. Specifying one set of data as transient (managed in memory), while choosing persistent storage for other record types, requires a simple database schema declaration.
Learn why starting with an in-memory database makes for a better hybrid system.