Here is a video where Philip Howard, Research Director at Bloor Research, evaluates performance, scalability, administration, and cost considerations for IBM Smart Analytics System and Oracle Exadata [for data warehouse environments]. This video is packed with great practical advice for evaluating these products.
Philip Howard, Research Director at Bloor Research, recently evaluated the performance, scalability, administration, and cost considerations for the leading integrated systems from IBM and Oracle for OnLine Transaction Processing (OLTP) environments. Here is a summary of his conclusions:
And here is a video with his evaluation. It is packed with practical advice regarding storage capacity, processing capacity, and more.
The NoSQL movement has garnered a lot of attention recently. It has been built around a number of emerging highly-scalable non-relational data stores. The movement is also providing a real lease of life for smaller non-relational database vendors who have been around for a while.
Last week, I noticed an entire track for XML and XQuery sessions at the recent NoSQLNow Conference in San Jose. If XML databases and XQuery are key constituents of the NoSQL world, does that mean that IBM DB2 and Oracle Database should be included in the NoSQL movement? After all, both IBM DB2 and Oracle Database store XML data and provide XQuery interfaces. Of course, I’m not being serious here. I don’t believe that the bastions of the relational world should be included in the NoSQL community. Are native XML databases, which have been around for a while, really in the spirit of the NoSQL movement? What’s your opinion?
I believe that the boundaries of the NoSQL community are perhaps a bit looser than they should be. Essentially, absolutely everything except relational databases are being grouped under the NoSQL banner. I can understand how this has happened, but do the NoSQL community really want to dilute their message by including all of these technologies, most of which have been around for quite some time and had relatively limited traction. In the spirit of what I believe is at the genesis of the current NoSQL movement, I reckon that a NoSQL solution should have the following characteristics:
– Not be based on the relational model
– Have little or no acquisition cost
– Be designed to run on commodity hardware
– Use a distributed architecture
– Support extreme or Web-scale databases
Notice that I don’t include a characteristic based on lack of consistency. I reckon that, over time, consistency will become a characteristic of some NoSQL environments.
By the way, earlier in this blog post I referred to the XML and XQuery capabilities in IBM DB2 and Oracle Database. In case you are curious, there is a significant difference in how DB2 and Oracle Database have incorporated XML capabilities in their respective products, with Oracle essentially leveraging their existing relational infrastructure to provide several ways to store XML data, while IBM built true native XML storage capabilities into its product. In other words, DB2 is indeed a true “native XML store”. In the past, I used to blog about native XML storage over at www.nativeXMLdatabase.com, before handing the reigns over to Matthias Nicola. If you want a little more insight on XML support in Oracle Database, check out XML in Oracle 11g and Why Won’t Oracle Publish XML Benchmark Results for TPoX?
Noel Yuhanna is one of the more prominent names in the database software industry. He is the principal analyst covering database software at Forrester. Here’s a 12-minute video where Noel describes his view on the most commonly used strategies for lowering your database-related costs. Topics include virtualized infrastructure, database compatibility layers, database-as-a-service, database compression, database sub-setting, and administration automation. This video is packed with interesting information. I hope you enjoy!
Here’s a short video that was recorded at the IDUG conference, where I talk about the characteristics of Big Data solutions, discuss some of the technologies involved, and describe some real world Big Data solutions that IBM has implemented. Its a high-level introduction, but if you’re not sure what this “Big Data” term refers to, you may find it useful.
In the video, I try to quantify what “big” means today, as well as describing some lessons we have learned while implementing Big Data solutions. Technologies introduced include Map/Reduce systems, systems for analyzing streaming data, Massive Parallel Processing data warehouse systems, and in-memory database systems.
Those of you that know me in person, will see that I was a little under-the-weather when the video was recorded. You can hear it in my voice, see it in my demeanor, and notice it in my cadence. I hope you can get past this, and find this video useful.
Last year, I blogged about how IBM DB2 has the Leading x86-based TPC-C Result. Well, IBM has further cemented DB2′s position as the leading database for x86-64 systems with a new record-breaking TPC-C benchmark result. The new benchmark result achieved more than 3 million transactions per minute on an IBM System x 3850 X5. The entire system for this result is housed in a single, space-saving 42U rack. The system runs DB2 9.7 on SUSE Linux. It has four Intel Xeon E7-8870 processors running at 2.40GHz (4 processors/40 cores/80 threads). It should also be noted that the system uses Solid State Drive (SSD) storage for faster database access.
For me, the most interesting aspect of this result is not just the performance; it is the price for that performance. And, of course, price/performance is a key consideration for all systems, but especially for cost-conscious x86-64 purchasing decisions. The new system costs US$0.59 per tpmC. As of today, this is the lowest cost of any system in the Top 10 TPC-C performance results (by the way, the next lowest cost also features DB2). See for yourself at TPC-C – Top Ten Performance Results.
If you look at the TPC-C – Top Ten Price/Performance Results, you will see some results from Oracle that offer better price/performance. However, these Oracle results are for very small benchmark systems; approximately one-tenth the size of the IBM DB2 systems. And they include only Oracle Database 11g Standard Edition One; whereas the IBM results include the full enterprise edition of DB2. Not only do the IBM benchmark system give you more product capability for your money, but you can clearly see that the performance of the IBM systems and the cost per transaction for the IBM systems both scale up very nicely.
IBM System x®3850 X5 (Intel Xeon E7-8870 processors 2.40GHz, 4 processors/40 cores/80 threads) TPC-C result of 3,014,684 tpmC, $.59 USD/tpmC, available 9/22/11, DB2 9.7, SUSE Linux® Enterprise Server 11 (SP1)
The International DB2 User Group (IDUG) and IBM are offering a complimentary workshop for DB2 for z/OS clients who are planning to migrate to DB2 10. This workshop will help attendees maximize the business benefits and cost savings associated with moving to DB2 10; it will also ensure that they are adopting IBM best practices when doing so. The workshop is being offered immediately prior to the IDUG DB2 Tech Conference EMEA in Prague. Seats are limited, so make sure to sign up soon! The details are:
Date: 13th November 2011
Time: 9:30 AM – 5:00 PM
Location: IDUG DB2 Tech Conference EMEA in Prague
Cost: Complimentary
Link: DB2 10 Migration Planning Workshop
Matt Asay wrote an interesting article for The Register titled SQL Survives Murder Attempt by Mutant Stepchild where he opines that “NoSQL remains a tiny blip in the overall datastore universe“. And he’s correct. When it comes to the universe of data management deployments, NoSQL usage is a tiny fraction of the overall data management market.
The term NoSQL implies that these emerging data management technologies are fighting the SQL establishment. I would argue that, instead, they are fighting the traditional Relational Database Management System (RDBMS) establishment. The NoSQL movement has evolved out of a loose association of technologies that solve challenges that traditional relational solutions are not designed to solve well. RDBMS software is good at addressing the majority of our data management challenges. However, there are instances where the relational approach simply does not work well. While these situations are a relatively small part of the data management universe, they are nonetheless important. After all, these emerging technologies are meeting a very real market need, and the likelihood is that this market need will grow as the business world shifts towards use cases where these NoSQL solutions shine. So, essentially we have a situation where a bunch of data management technologies are emerging to solve a subset of data management challenges that are not well served by currently available technologies. I expect that some of these NoSQL use cases will evolve into reasonable, if relatively small, segments of the overall data management market.
To further illustrate that the term NoSQL is probably a misnomer, some of these NoSQL technologies have plans to adopt SQL interfaces. How will the NoSQL movement react when some of its products start adopting SQL interfaces? As Alanis Morissette would say, isn’t it ironic!
But anyway, back to the topic at hand. While certain segments of the high tech media are portraying this as a big battle between the incumbent and a challenger, I would instead portray it as the emergence of new technologies to augment the incumbent. The NoSQL solutions are essentially a set of technologies that address use cases that are not well served by existing relational technology. The relational database software market is huge today, and I don’t see this changing in any significant way in the foreseeable future. Despite what some wide-eyed and naive smaller vendors may claim, these emerging technologies are simply not in a position to wholesale unseat the incumbent relational database technology. Instead, they will likely augment relational technology in many IT environments. In some IT environments, where their business is built around NoSQL-friendly use cases, it may actually be the opposite with relational technologies augmenting the more dominant NoSQL technologies. However, as Matt points out in his article, the fact that SQL-based systems have such a low barrier-to-entry will ensure their long-term dominance. Another significant factor in determining how thing will evolve is the huge investment and significant maturity of the ease-of-use, ease-of-maintenance, stability, reliability, and security features that make RDBMS systems enterprise-ready today. And don’t forget that, as emerging technologies play catch-up with this huge investment, the relational vendors will continue to innovate.
In my opinion, the likely outcome here is that there will be a set of separate battles among vendors for each of the individual market segments corresponding to the NoSQL use cases. And the larger vendors will participate in the more lucrative of these market segments, either with organically-developed or acquired products. And, for the most part, the servicing of these use cases will be relatively independent of the larger relational database market. What’s you opinion?