Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: NoSQL, NewSQL and NuoDB
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Software > SQL > NoSQL, NewSQL and NuoDB
SoftwareSQL

NoSQL, NewSQL and NuoDB

Barry Devlin
Barry Devlin
0 Min Read
SHARE

susurration.<p><span class=susurration.jpgIt seems to me that much of the drive behind NoSQL (whether No SQL or Not Only SQL) arose from a rather narrow view of the relational model and technology by web-oriented developers whose experience was constrained by the strengths and limitations of MySQL. Many of their criticisms of relational databases had actually been overcome by commercial products like DB2, Oracle and Teradata to varying extents and under certain circumstances. Although, of course, open source and commodity hardware pricing also continue to drive uptake.

A similar pattern can be seen with NewSQL in its original definition by Matt Aslett of the 451 group, back in April 2011. So, when it comes to products clamoring for inclusion in either category, I tend to be somewhat jaundiced. A class defined by what it is not (NoSQL) presents some logical difficulties. And one classed “new”, when today’s new is tomorrow’s obsolete is not much better. I prefer to look at products in a more holistic sense. With that in mind, let’s get to NuoDB, which announced version 2 in mid-October. With my travel schedule I didn’t find time to blog then, but now that I’m back on terra firma in Cape Town, the time has come!

Back in October 2012, I encountered NuoDB prior to their initial launch, and their then positioning as part of the NewSQL wave. I also had a bit of a rant then about the NoSQL/NewSQL nomenclature (although no one listened then either), and commented on the technical innovation in the product, which quite impressed me, saying “NuoDB takes a highly innovative, object-oriented, transaction/messaging-system approach to the underlying database processing, eliminating the concept of a single control process responsible for all aspects of database integrity and organization. [T]he approach is described as elastically scalable – cashing in on the cloud and big data.  It also touts emergent behavior, a concept central to the theory of complex systems. Together with an in-memory model for data storage, NuoDB appears very well positioned to take advantage of the two key technological advances of recent years… extensive memory and multi-core processors.”

The concept of emergent behavior (the idea that the database could be anything anybody wanted it to be, with SQL simply as first model) was interesting technically but challenging in positioning the product. Version 2 is more focused, with a tagline of distributed database and an emphasis on scale-out and geo-distribution within the relational paradigm. This makes more sense in marketing terms and the use case in a global VoIP support environment shows how the product can be used to reduce latency and improve data consistency. No need to harp on about “NewSQL” then…

More Read

Image
Is the end of traditional enterprise software near?
Is Hadoop Knowledge a Must-Have for Today’s Big Data Scientist?
Not All Hadoop Users Drop ACID
The Challenges and Solutions of Big Data Testing
Big Data Analytics – Volume, Variety, Velocity

Sales aside, the underlying novel technical architecture continues to interest me. A reading on the NuoDB Technical Whitepaper (registration required) revealed some additional gems. One, in particular, resonates with my thinking on the ongoing breakdown of one of the longest-standing postulates of decision support: the belief that operational and informational processes demand separate databases to support them, as discussed in Chapter 5 of my book. While there continue to be valid business reasons to build and maintain a separate store of core, historical information, real-time decision needs also demand the ability to support both operational and informational needs on the primary data store. NuoDB’s Transaction Engine architecture and use of Multi-Version Concurrency Control together enable good performance of both read/write and longer-running read-only operations seen in operational BI applications.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data analytics for pharmacy trends
How Data Analytics Is Tracking Trends in the Pharmacy Industry
Analytics Big Data Exclusive
ai call centers
Using Generative AI Call Center Solutions to Improve Agent Productivity
Artificial Intelligence Exclusive
warehousing in the age of big data
Top Challenges Of Product Warehousing In The Age Of Big Data
Big Data Exclusive
car expense data analytics
Data Analytics for Smarter Vehicle Expense Management
Analytics Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Image
Business IntelligenceITSoftware

Redefining Logistics Services through IT Innovation

3 Min Read
Image
Best PracticesBig DataData WarehousingHadoopMarket ResearchPrivacy

My 7 Big Data Favorites of 2014

3 Min Read
Image
AnalyticsBig DataData ManagementData MiningData QualityData WarehousingExclusiveHadoopPredictive Analytics

The Driving Force Behind Big Data: Data Connectivity

8 Min Read

Resampling Data in Hadoop with RHadoop

1 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?