Data & Intelligence

SQL, NoSQL, and NewSQL

Traditional SQL databases and data warehouses have been around for decades and have been doing really well. However, Big Data NoSQL changed the game with big returns for big investments. Concepts like Edge Analytics have been game changers “uberizing” foundational changes in business models.

I recently attended a conference hosted by Snowflake, a data warehouse vendor revolutionizing the cloud data warehouse industry. Interestingly, data warehousing is changing from traditional star and snowflake models (Kimball and Inmon) to Big Data warehousing, and now to comprehensive cloud data warehousing. While quite a few of my clients say, “cloud is cloudy”, companies like Salesforce, Microsoft, and Amazon need little justification for moving to the cloud with their market share.

Cloud data warehouses are revolutionizing the industry with the concept of NewSQL, which uses traditional SQL with elasticity like NoSQL. After gaining experience with these options, here are my views on the databases:

SQL

Pros:

  • Proven database technologies with standard ANSI SQL support
  • Ad-hoc querying (business and IT)
Data Intelligence - The Future of Big Data
The Future of Big Data

With some guidance, you can craft a data platform that is right for your organization’s needs and gets the most return from your data capital.

Get the Guide

Cons:

  • Significant issues with scalability
  • Complex tuning techniques

NoSQL

Pros:

  • 99% availability and significant scalability
  • Optimized to support structured, semi-structured, and unstructured data

Cons:

  • Evolving programming languages with significant custom coding
  • Lacks ACID (Atomicity, Consistency, Isolation, Durability) database transactions

NewSQL

Pros:

  • Easy to use scalability and availability eliminating DBA needs
  • In memory analytics utilizing Big Data infrastructure
  • Standard ANSI SQL features providing easy to use interactions for business and IT users

Cons:

  • A combination of traditional SQL and Big Data capabilities offers significant challenges on data governance
  • Giving business capabilities to process unlimited data without “teaching them to fish” offers challenges in operations
  • Concerns on security at an enterprise level

 

About the Author

Arvind Murali is the Chief Data Strategist for Data Governance with Perficient. His role includes defining data strategy and governance to deliver transformative data platforms. Arvind has served as an executive advisor for data strategy and governance to organizations across several industries. Arvind’s dedication to solving challenges and identifying new opportunities has provided valuable business-focused results for clients, such as providing self-service access to data for global sales teams; helping physicians create informed wellness plans; and delivering insights about current supply chain inventories. He is a passionate Vlogger on YouTube and discusses real-world insights, data platform trends, and the importance of governance as big data continues its exponential growth.

More from this Author

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Subscribe to the Weekly Blog Digest:

Sign Up