Embedded Database White Papers

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.

McObject Breaks In-Memory Database Boundaries in New Benchmark
In-memory database systems (IMDSs) hold out the promise of breakthrough performance for time-sensitive, data-intensive tasks. Yet IMDSs’ compatibility with very large databases (VLDBs) has been largely uncharted. This benchmark analysis fills the information gap and pushes the boundaries of IMDS size and performance. Using McObject’s 64-bit eXtremeDB-64, the application creates a 1.17 Terabyte, 15.54 billion row database on a 160-core Linux-based SGI® Altix® 4700 server. It measures time required for database provisioning, backup and restore. In SELECT, JOIN and SUBQUERY tests, benchmark results range as high as 87.78 million query transactions per second. The report also examines efficiency in utilizing all of the test bed system’s 160 processors, and includes full database schema and relevant application source code.

Data Management in Set-Top Box Electronic Programming Guides
The electronic programming guide (EPG) enables digital television users to search, filter and customize program listings and even control access to content. These capabilities entail significant real-time data management, and a handful of vendors have incorporated commercial, off-the-shelf (COTS) databases in their set-top boxes. This report presents lessons learned in such projects, mapping emerging digital TV standards, set-top box data management requirements, and typical data objects and interrelationships. Sample code and embedded database schema focus on efficiencies gained by implementing EPG data management using an in-memory database.

Embedded Software Development: Balancing Process-Centric and Data-Centric Approaches
In embedded software development, it pays to balance process-centric and data-centric viewpoints. “Process-centric” emphasizes system logic and can prevent unstructured (spaghetti) code; “data-centric” focuses how the system ingests, transforms and stores data, and can reduce redundancy, complexity, and errors. For best results, developers are guided by both outlooks. This white paper uses IBM Rational's Rhapsody in C Unified Modeling Language tool and McObject’s eXtremeDB to illustrate the blended approach, with practical examples.

The Role of In-Memory Database Systems for Routing Table Management in IP Routers
Core Internet bandwidth grows at triple the rate of CPU power, but high-value applications depend on managing much more data traffic at the network's edge. This requires rapid evolution of routing table management (RTM) software within IP routers. This paper examines using in-memory database systems (IMDS) to add RTM development flexibility, data integrity and fault tolerance. It provides performance examples on Linux and Windows 2000. This embedded database solution adds to vendors’ ability to produce new generations of routers faster and at less cost, improving their competitive position.

Real-time Databases For Embedded Systems
Real-time systems are now used in many application domains, including network infrastructure, telecommunications and financial markets. As real-time systems evolve, their applications become more complex, and often require timely processing of massive amounts of data. This white paper examines real-time systems’ embedded database needs; emerging commercial real-time database systems (RTDBSs) vs. traditional databases; the implications of “hard” vs. “soft” real-time; and the role of RTDBSs in applications including process control, spacecraft control, and telecommunications.

Data Management for Military and Aerospace Embedded Systems
This white paper examines the data management needs of military and aerospace embedded systems, and focuses on existing and emerging data management technology and its suitability to meet these requirements.

Main Memory vs. RAM-Disk Databases: A Linux-based Benchmark
A new type of DBMS, the in-memory database system (IMDS, or all-in-RAM database), claims breakthrough performance and availability via memory-only processing. But doesn't database caching, or using a RAM-disk, achieve the same result with a traditional (disk-based) database? This benchmark tests eXtremeDB against a widely used embedded database, in both disk-based and RAM-disk modes. Deployment on RAM-disk boosts the traditional database by as much as 74 percent, but it still lags the IMDS substantially. Read about the architectural reasons for this disparity.

Re-Inventing Data Management For Intelligent Devices
Intelligent devices such as set-top boxes, consumer electronics, and networking gear are adding software "smarts" and managing larger volumes of more complex data –a challenge typically met with embedded database management systems (DBMS). But traditional databases, with roots in business processing, present CPU and memory requirements that are too expensive for price-sensitive high-tech gear. This paper examines the emerging on-device database requirements, and looks at one in-memory database, eXtremeDB, developed in response to these needs.

SQL or Navigational Database APIs: Which Best Fits Embedded Systems?
For embedded systems developers, the choice of database application programming interfaces (APIs) often boils down to the high-level SQL language and Call Level Interface, and navigational APIs integrated with C++ and other languages. Which API is best? This paper examines the familiarity and ease-of-use often cited as benefits of SQL. A sample application is implemented with SQL and then with a navigational API, to explore the issues of programming ease, maintainability, determinism and learning curve. Special attention is given to the significance of SQL optimizers in evaluating embedded database APIs.