How to Scale Different Data Models:
Architecting For Scalability & Elasticity
Posted by
EdmontonPM
Feb 23
Live Webinar March 2nd 2017 1:00 PM – 2:00 PM EST
Activity Type: Education – Course or Training 1 Hour 1 PDU free
Provider: O’Reilly
Achieving scalability and elasticity is a huge challenge for data architects. Data just isn’t small, neat, and orderly anymore.
While all database vendors say they scale big, what if you want to scale to handle over 6,000 queries per second?
Once you are processing data at this speed, how do you handle bottlenecks exhibited under sustained or bursting loads?
If you are running into these issues, it might be because you are adding unnecessary steps in the process.
In this webcast, join Greg Meddles, (O’Reilly bio) Sr. Principal Consultant for MarkLogic, to learn how complex applications and systems must be designed to scale horizontally — both at the software and the hardware level. This concept of “scaling through parallelism” is crucial for performance. Greg will also discuss how to maximize your use of data models you already have, to avoid converting them for every individual query.
Learn:
- How to scale through “parallelism”
- How data models scale differently, and how to test for each type of resource
- Techniques for scaling across different environments, including on-premises or in the cloud
- Best practices and tests for finding bottlenecks in a data pipeline
Presenter: Greg Meddles, Sr. Principle Consultant MarkLogic: thrives when solving difficult problems. Greg brings implementation experience as both a consultant and product engineer for customers ranging from the financial sector, Intelligence Community, and healthcare. Greg has an interest in semantics, artificial intelligence, and natural language understanding. Greg holds a Bachelor’s Degree in Mathematics from Birmingham-Southern College.
Click to register for:
How to Scale Different Data Models:
Architecting For Scalability & Elasticity
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