In-Memory Database Systems
In the event of a catastrophic failure, such as loss of power, a disk-based database recovers by committing complete transactions or rolling back partial transactions from log files when the system restarts. Disk-based databases are hard-wired to keep transaction logs, to flush transaction log files and to cache to disk after transactions are committed.
Main memory databases also provide transactional integrity. To do this, the IMDS maintains a before image of the objects that are updated or deleted and a list of database pages added during a transaction. When the application commits the transaction, the memory for before images and page references returns to the memory pool (a fast and efficient process). If an in-memory database must abort a transaction (for example, if the inbound data stream is interrupted), the before images are restored to the database and the newly inserted pages are returned to the memory.
In the event of catastrophic failure, the in-memory database image is lost. This is a major difference from disk-based databases. If the system is turned off, the IMDS is reprovisioned upon restart. Consequently, there is no reason to keep transaction log files, and another complex, memory-intensive task is eliminated from the IMDS.
This functionality may not suit every application, but in the embedded systems arena, examples abound of applications with data stores that can be easily replenished in real time. These include a program guide application in a set-top box that downloads from a satellite or cable head-end, a wireless access point provisioned by a server upstream or an IP routing table that is repopulated as protocols discover network topology. Developers of such systems gladly limit the scope of transaction processing in exchange for superior performance and a smaller footprint.
This does not preclude the use of saved local data. With an IMDS, the application can open a stream (a socket, pipe or a file pointer) and instruct the database runtime to read or write a database image from or to the stream. This feature could be used to create and maintain boot-stage data, i.e., an initial starting point for the database. The other end of the stream can be a pipe to another process or a filesystem pointer (any filesystem, whether it's magnetic, optical or Flash).
Where and how can IMDS technology make a difference? While in-memory databases have cropped up in various application settings, the following scenario, involving embedded software in the most common internet infrastructure device—the IP router, offers an idea of the problems this technology can address.
Modern IP routers incorporate routing table management (RTM) software that accomplishes the core task of determining the next hop for data packets on the Internet and other networks. Routing protocols continuously monitor available routes and the status of other routing devices, then update the device's routing table with current data.
These routing tables typically exist as proprietary outgrowths of the RTM software. This solution is one of the principal challenges in developing next-generation routers. As device functionality increases, routing table management presents a significant programming bottleneck. Lacking support for the complex data types and multiple access methods that are hallmarks of databases, self-developed routing table management (RTM) structures provide a limited toolset.
In addition, like any data management solution that is hard-wired to the application it supports, routing tables encounter difficulties in extensibility and reliability. Changes made to the data management code reverberate through the entire RTM structure, causing unwanted surprises and adding to QA cycles. Scalability is also an issue: self-developed data management that works well for a given task often stumbles when the intensity of use is ratcheted up. The result is that while the Internet's growth requires rapid advances in routing technology, this device evolution is slowed by software architecture that has outlived its usefulness.
Under such conditions, using a database would seem to be a no-brainer. But deploying a traditional DBMS within an IP router is problematic. Real-time internet address lookups won't accommodate the latency required to go to disk and perform the caching, transaction logging and other processes that are part and parcel of disk-based DBMSes.
In addition, imposing a large database footprint within the router necessitates more RAM and a more powerful CPU. This adds to the overall device cost, and the market for routers is price-competitive. Even a slightly lower per-unit price increases the manufacturer's market share, and a lower per-unit cost drops right to the bottom line. Software that saves RAM, or requires a less expensive processor, can determine product success.
The emergence of in-memory databases allows the application of DBMS technology to many embedded systems. For developers of embedded systems, proven database technology provides benefits including optimized access methods and data layout, standard and simplified navigation methods, built-in concurrency and data integrity mechanisms, and improved flexibility and fault tolerance. Adoption of this new breed of DBMS simplifies embedded system development while addressing growing software complexity and ensuring high availability and reliability.
Steve Graves is president and cofounder of McObject, developer of the eXtremeDB in-memory database system. As president of Raima Corporation, he helped pioneer the use of DBMS technology in embedded systems, working closely with companies in building database-enabled intelligent devices. A database industry veteran, Graves has held executive-level engineering, consulting and sales/marketing positions at several public and private technology companies.
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