Relatives Got You Down? Check Out BigQuery and Redshift

December 25, 2018

I read “Redshift Vs BigQuery: What Are The Factors To Consider Before Choosing A Data Warehouse.” With Oracle on the ropes and database technology chugging along, why pay attention to old school solutions?

The article sets out to compare and contrast BigQuery (one of the Google progeny known to have consorted with a certain Mr. Dremel.) Amazon has more database products and services than I can keep track of. But RedShift is one of them, and it is important if an intelware company uses AWS and the RedShift technology.

Which system is more “flexible”? I learned:

In the case of Redshift, if anything goes kaput during a transaction, Amazon Redshift allows users to perform roll-back to ensure that data get backs to the consistent state. BigQuery works on the principle of append-only data and its storage engine strictly follows this technique. This becomes a major disadvantage to the user when something goes wrong during the transaction process, forcing them to restart from the beginning or specific point. Another key point is that duplicating data in BigQuery is hard to achieve and costly. Both the technologies have reservations regarding insertion of streaming data, with Redshift taking edge by guaranteeing storage of data with additional care from the user. On the other hand, BigQuery supports de-duplication of streaming data in the most effective way by using time window.

The write up points out:

As compared to BigQuery, Redshift is considerably more expensive costing $0.08 per GB, compared to BigQuery which costs $0.02 per GB. However, BigQuery offers only storage and not queries. The platform charges separately for queries based upon processed data at $5/TB. As BigQuery lacks indexes and various analytical queries, the scanning of data is a huge and costly process. In most cases, users opt for Amazon Redshift as it is predictable, simple and encourages data usage and analytics.

Which is “better”? Not surprisingly, both are really swell. Helpful. But the Beyond Search goose was curious about:

Performance
Latency for different types of queries
Programming requirements

But swell is fine.

Stephen E Arnold, December 25, 2018

Written by Stephen E. Arnold · Filed Under Amazon, Database, Google, News

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Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.