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
    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
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The End of Relational Databases?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > The End of Relational Databases?
Business IntelligenceData Mining

The End of Relational Databases?

Timo Elliott
Timo Elliott
4 Min Read
SHARE

hasso-banner

Hasso Plattner, SAP’s co-founder, chairman, and “Chief Software Advisor” has been giving a series of talks including his keynote at SAPPHIRE 2009 on why in his view “disk has become yesterday’s tape”, and why column storage and in-memory techniques are the future for both data warehousing AND enterprise applications, displacing the 20-year reign of relational databases.

imageExperts have advocated column databases such as Sybase IQ and LucidDB for data warehousing for many years.

But now, based on research done at the his Institute (and a lifetime of trying to get the best performance possible for enterprise applications), Plattner is advocating basing both OLAP and OLTP systems on column storage in order to eliminate the need for the cumbersome ETL process, and reduce system complexity and the number of database tables.

More Read

Data Mining Improved Company’s Revenue By 187%
Artificial Intelligence, Business, And Our Future Job Security
Government IT Savings Success – Time to Open the Piggy Bank…Carefully
Why XML is incompatible with big data
Building a Customer-Centric Systems Architecture

More details are available in his white paper A Common Database Approach for OLAP and OLTP Using an In-Memory Column Database and a related presentation. The research was conducted using SAP’s TREX technology and real customer data (to see what the technology can do in a business intelligence context, check out SAP BusinessObjects Explorer)…

hasso-banner

Hasso Plattner, SAP’s co-founder, chairman, and “Chief Software Advisor” has been giving a series of talks including his keynote at SAPPHIRE 2009 on why in his view “disk has become yesterday’s tape”, and why column storage and in-memory techniques are the future for both data warehousing AND enterprise applications, displacing the 20-year reign of relational databases.

imageExperts have advocated column databases such as Sybase IQ and LucidDB for data warehousing for many years.

But now, based on research done at the his Institute (and a lifetime of trying to get the best performance possible for enterprise applications), Plattner is advocating basing both OLAP and OLTP systems on column storage in order to eliminate the need for the cumbersome ETL process, and reduce system complexity and the number of database tables.

More details are available in his white paper A Common Database Approach for OLAP and OLTP Using an In-Memory Column Database and a related presentation. The research was conducted using SAP’s TREX technology and real customer data (to see what the technology can do in a business intelligence context, check out SAP BusinessObjects Explorer).

Given that the vast majority of relational databases are used for OLTP transactions today, this would represent a radical change for the enterprise application market.

And although data warehousing will still need to exist, because of master-data management, data synchronization, data quality, etc., it would certainly be a lot simpler, and a lot faster, since much of it could be done directly on the “transactional” data source.

While nobody has promised that SAP will develop the concept as a product, Plattner has presented his views widely to SAP employees, and leaves no doubt that he thinks this is the way ahead.

Here’s the last slide of Hasso’s presentation at the recent SIGMOD 2009 conference for database researchers – this is  certainly something that we’ve been looking forward to for a while…

image

[Post to Twitter] Was this interesting? Share with others on Twitter with automatic URL shortening! 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Why the AI Race Is Being Decided at the Dataset Level
Why the AI Race Is Being Decided at the Dataset Level
Artificial Intelligence Big Data Exclusive
image fx (60)
Data Analytics Driving the Modern E-commerce Warehouse
Analytics Big Data Exclusive
ai for building crypto banks
Building Your Own Crypto Bank with AI
Blockchain Exclusive
julia taubitz vn5s g5spky unsplash
Benefits of AI in Nursing Education Amid Medicaid Cuts
Artificial Intelligence Exclusive News

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

big data and business intelligence
AnalyticsBig DataBusiness Intelligence

Can Business Intelligence Answer the Questions Asked of it Without Big Data?

6 Min Read

Be Prepared to Duel with Data Quality

10 Min Read

Interview –Michael Zeller CEO,Zementis

11 Min Read
data tools
AnalyticsBest PracticesBig DataBusiness IntelligenceCulture/LeadershipData ManagementData MiningData VisualizationDecision ManagementKnowledge Management

Democratizing Data with Decision Management

6 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 in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

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?