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
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Graph Databases and the Future of Large-Scale Knowledge Management
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Graph Databases and the Future of Large-Scale Knowledge Management
Uncategorized

Graph Databases and the Future of Large-Scale Knowledge Management

TonyBain
TonyBain
3 Min Read
SHARE

Los Alamos National LaboratoryImage via Wikipedia

Todd Hoff has posted a link to a Los Alamos National Lab presentation on Graph Databases. In this paper they provide a revisit on the classic RDBMS vs Graph database debate.

The Relational Database hasn’t maintained its dominance out of dumb luck. Instead, the RDBMS has consistently outperformed while providing the most general use capability of all the variety of platforms that have been available. Many other approaches have been tried; often, these have provided better object model integration (OODBMS) or better data model representation. But when the rubber has hit the road they have failed on one or more of the key staples of a DBMS – performance, scalability, security, reliability, recoverability and ease of use.

Right now there seems to be more focus and traction than ever before to get it right. Graph databases are interesting and clearly have value in solving the hierarchal abstraction problem currently encountered when modeling such structures in the RDBMS. In other aspects they do share some similarities with the hybrid DHT’s. I think a mix of the best of several approaches will be something interesting (of course it will have to perform …

More Read

Blinded
Why change management needs design thinking
Data Visualizations: The Tip of the Iceberg of Understanding
Microsoft and the Revolution: Analytics
More intelligent processes – a video and presentation

Los Alamos National LaboratoryImage via Wikipedia

Todd Hoff has posted a link to a Los Alamos National Lab presentation on Graph Databases. In this paper they provide a revisit on the classic RDBMS vs Graph database debate.

The Relational Database hasn’t maintained its dominance out of dumb luck. Instead, the RDBMS has consistently outperformed while providing the most general use capability of all the variety of platforms that have been available. Many other approaches have been tried; often, these have provided better object model integration (OODBMS) or better data model representation. But when the rubber has hit the road they have failed on one or more of the key staples of a DBMS – performance, scalability, security, reliability, recoverability and ease of use.

Right now there seems to be more focus and traction than ever before to get it right. Graph databases are interesting and clearly have value in solving the hierarchal abstraction problem currently encountered when modeling such structures in the RDBMS. In other aspects they do share some similarities with the hybrid DHT’s. I think a mix of the best of several approaches will be something interesting (of course it will have to perform extremely well and have great developer support).

It’s such an interesting time to be in data management.

Reblog this post [with Zemanta]


Link to original postInnovations in information management

TAGGED:rdbmsrelational database
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai in video game development
Machine Learning Is Changing iGaming Software Development
Exclusive Machine Learning News
media monitoring
Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
Analytics Exclusive Infographic
data=driven approach
Turning Dead Zones Into Data-Driven Opportunities In Retail Spaces
Big Data Exclusive Infographic
smarter manufacturing
Connecting the Factory Floor: Efficient Integration for Smarter Manufacturing
Infographic News

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Big Data and the Wizard of Oz Syndrome

4 Min Read

#14: Here’s a thought…

6 Min Read

The Total Cost of Big Data Performance [VIDEO]

1 Min Read

Recently Read 02/10/2010

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.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?