Introduction to the Firebird Database
Many solutions for replication have been developed by various entities. Most of these rely on trigger-based mechanisms that keep track of inserts, updates or deletes from a given table and then take those changes and propagate them to another database. As far as I can determine, all of the solutions are commercial in nature and can be used to administer databases on different platforms, including Window and UNIX/Linux. Additional information on this can be found on the IBPhoenix Web site (see Resources).
A single database can span to the data files, which gives the administrator the flexibility to load balance the database from a disk perspective. It is not unusual for databases to have local hot spots where an inordinate amount of activity occurs. Having the database laid out on multiple data files, which could reside in turn on multiple disks, alleviates the problem to a certain extent. Additionally, a single table also can be put on a separate file, and in this way load can be distributed to an even finer granularity.
Some people might wonder why they should make the effort to learn a new database, especially if they already are familiar with MySQL or PostgreSQL. From my perspective, Firebird offers a comfortable migration path from closed-source, commercial databases to an open-source database. I have found the task of converting from Oracle or Sybase to MySQL or PostgreSQL to be a bit daunting, as the nature of these databases is quite different from the commercial offerings. If the reader already is familiar with any of the large popular RDBMSs, the concepts he or she has learned over the years in those databases can convert smoothly to Firebird It offers virtually every common feature available in high-end databases without any significant impact on performance, as compared to the speed demons of the Linux platform. If you are looking for a database for your next project, think about Firebird as a viable option.
|Non-Linux FOSS: libnotify, OS X Style||Jun 18, 2013|
|Containers—Not Virtual Machines—Are the Future Cloud||Jun 17, 2013|
|Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer||Jun 12, 2013|
|Weechat, Irssi's Little Brother||Jun 11, 2013|
|One Tail Just Isn't Enough||Jun 07, 2013|
|Introduction to MapReduce with Hadoop on Linux||Jun 05, 2013|
- Containers—Not Virtual Machines—Are the Future Cloud
- Non-Linux FOSS: libnotify, OS X Style
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Linux Systems Administrator
- Introduction to MapReduce with Hadoop on Linux
- RSS Feeds
- Weechat, Irssi's Little Brother
- Tech Tip: Really Simple HTTP Server with Python
- Validate an E-Mail Address with PHP, the Right Way
- Android's Limits
- Reply to comment | Linux Journal
39 min 25 sec ago
- Welcome to 1998
1 hour 27 min ago
- notifier shortcomings
1 hour 51 min ago
3 hours 28 min ago
- Android User
3 hours 30 min ago
- Reply to comment | Linux Journal
5 hours 23 min ago
8 hours 12 min ago
- This is a good post. This
13 hours 25 min ago
- Great, This is really amazing
13 hours 27 min ago
- These posts are really good
13 hours 29 min ago
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?