Why relational databases make sense for big data?

by Hongde H
In the article  ” Why relational databases make sense for big data”, Dave Rosenberg talked about the “big data” trend that more and more organizations are now (or soon will be) dealing with managing and extracting information from databases that are growing into the multi-petabyte range. This trend caused developers are forced to seek new “NoSQL” approaches and instead process data in a distributed manner. These so called “NoSQL” such as Cassandra and MongoDB databases, are built to scale easily and handle massive amounts of data in a highly fluid manner. Dave stated himself as a NoSQL supporter but he also pointed out that there is often a point where all of this data needs to be aggregated and parsed for different reasons, in a more traditional SQL data model.

Dave also mentioned that he get caught up by EnterpriseDB CEO Ed Boyajian through email. In the email, Boyajian stated four points of relational database management system:

1. Relational databases and ad-hoc queries

The data structure of the relational database is ideal for creating ad hoc queries. Once tables have established links between them, a user or programmer can retrieve related data as needed. Relational databases can assist business owners, managers and supervisors with quick query requests by collecting and displaying sales data, employee performance data or production data when needed.

2. SQL reduces development time and improves interoperability

SQL has been one of the most popular and successful computer languages of all time and writing an SQL query is typically simpler and faster than writing an algorithm to compute the desired answer, as is often necessary for data stores that do not include a query language.

3. Relational databases are mature, battle-tested technology

Most relational databases have been around for a decade  with very stable code bases and they are known to be relatively bug-free, and their failure modes are well understood.

4. Relational databases conform to widely accepted standards

According to Dave, many applications can be migrated with fairly straightforward changes. When they can’t, products and services to simplify the process are available from a variety of vendors.

Document databases and distributed key-value stores have different interfaces, offer different isolation and durability guarantees, and accept very different types of queries. Changing between such different systems promises to be challenging. (Boyajian)

The article does raise my attention on both NoSQL and SQL, which we will focus a lot in the course.  As time goes by, there are more and more different approaches coming up to deal with fast growing data. In order to organize our database well and effectively, we need to have a better understanding of any approach.

Source: Rosenberg, Dave (October 6, 2010) ” Why relational databases make sense for big data”

Retrieved from: http://news.cnet.com/8301-13846_3-20018846-62.html

2 thoughts on “Why relational databases make sense for big data?

  • October 28, 2012 at 10:19 pm

    Thanks for the article. One of the most common arguments made for relational databases is that writing a simple query is simpler and faster because it’s been around longer. Although it makes sense, I would consider that as a fallacy. I’m sure that once you learn and practice with NoSQL (or anything else for that matter), things would become just as easy. In fact, writing queries is becoming less and less necessary (at least in web development) as more and more frameworks such as Ruby on Rails use api’s that essentially write the queries in the syntax of your DBMS of choice.

  • October 28, 2012 at 10:20 pm

    Nice post. Relational databases are the most widely accepted in the business, but a friend who works in the business recently told me that sooner or later relational databases will no longer be useful. It’s time to move on to faster more efficient databases. Supposedly Facebook already is using a non relational database.

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