If there's one central theme in my blog, it's that modern DBMS alternatives should in many cases be used instead of the traditional market leaders... Here's a summary, reproduced from my most recent white paper, on what kinds of database management system you should use in which circumstances.
If there's one central theme in my DBMS2 blog, it's that modern database management system alternatives should in many cases be used instead of the traditional market leaders. So it was only a matter of time before somebody sponsored a white paper on that subject. The paper, sponsored by EnterpriseDB (disclosure noted), is now posted along with my other recent white papers. Its conclusion - summarizing what kinds of database management system you should use in which circumstances - is reproduced below.
Many new applications are built on existing databases, adding new features to already-operating systems. But others are built in connection with truly new databases. And in the latter cases, it's rare that a market-leading product is the best choice. Mid-range DBMS (for OLTP) or specialty data warehousing systems (for analytics) are usually just as capable, and much more cost-effective. Exceptions arise mainly in three kinds of cases:• Small enterprises with very limited staff.
• Large enterprises that have negotiated heavily-discounted deals for a market-leading product.
• Super-high-end OLTP apps that need absolute top throughput (or security certifications, etc.)
Otherwise, the less-costly products are typically the wiser choice.
In the analytics area, appliances and other specialty data warehousing products offer huge price/performance advantages over general-purpose systems. What's more, their superior performance allows them to get by with much simpler indexing structures, greatly reducing administrative burdens. If you have a data warehouse - or just a collection of data marts - running on Oracle or Sybase Adaptive Server or Microsoft SQL Server, it's likely you could do yourself a huge favor by moving it to a specialty system.
If you're an ISV, selling copies of the same software to many different customers, you should not be locked into an expensive market-leading DBMS. Whatever the remaining deficiencies of mid-range systems, at least one of them will surely be good enough to support your software with an acceptably low level of one-time porting effort. What's more, besides saving license and maintenance fees, a mid-range DBMS may be easier for your customers to operate than a complex, market-leading product.
The one area where it may be premature to port away from market-leading DBMS is in-house OLTP applications. The first rule for OTLP apps is that they MUST NOT BREAK, so if they're not broken, it's advisable to be cautious about fixing them. In some cases prompt porting is a good idea anyway, but often there will be lower-hanging fruit elsewhere in the enterprise.
As you may imagine, this paper contains only a small fraction of our analysis of DBMS alternatives. Indeed, that's the main topic of my DBMS2 blog. Specific recommended links include:
• The first of an extensive series of blog posts about database diversity, containing links to many of the rest (most of which are by me, but a couple of which are by database pioneer Michael Stonebraker).
• My coverage of data warehousing
• My coverage of mid-range database management systems If there's one central theme in my blog, it's that modern DBMS alternatives should in many cases be used instead of the traditional market leaders... Here's a summary, reproduced from my most recent white paper, on what kinds of database management system you should use in which circumstances.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
InformationWeek Must Reads Oct. 21, 2014InformationWeek's new Must Reads is a compendium of our best recent coverage of digital strategy. Learn why you should learn to embrace DevOps, how to avoid roadblocks for digital projects, what the five steps to API management are, and more.