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Why Large-Scale Applications Still Rely on SQL Databases

This article explores the enduring relevance of SQL in large-scale applications, highlighting why major platforms like Facebook and Twitter continue to use SQL despite the rise of NoSQL alternatives. It examines the scalability of SQL through parallel processing, relaxed data consistency constraints, and effective data and functional partitioning. The authors argue that SQL offers substantial advantages for handling large datasets and that strategies like distributed processing and service brokers enhance its scalability and performance, ensuring its prominent role in the industry.

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Why Large-Scale Applications Still Rely on SQL Databases

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  1. How do large-scale sites and applications remain SQL-based? G3 Alex Breyfogle & Kao-Ying Chen Rys, Michael. “Scalable SQL:How do large-scale sites and applications remain SQL-based?,” Communications of the ACM. Vol. 54 No. 6, Pages 48-53 10.1145/1953122.1953141. Web. 10 Feb. 2014.

  2. Why does the industry still use SQL? • Relevance: Relational Databases, Usage. • NoSQL databases claim to have higher scalability than traditional SQL databases • Yet giant social media sites such as Facebook and Twitter still use SQL

  3. Parallel Processing to Scale-up SQL • Parallel Processing (chapter 15) • Relaxing Data Consistency Constraints (chapter 8)

  4. Relaxing Data Consistency • Data and Functional Partitioning can allow more data flexibility

  5. Scale-Up: Distributed Processing to Scale-up SQL • Service Broker allows for asynchrony and high scalability

  6. In the End • SQL is still used widely in large scale databases • SQL can be up-scaled by taking advantage of parallel processing and relaxed data consistency constraints

  7. Questions?

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