Typical Amazon Redshift performance tuning challenges
Amazon Redshift has made great leaps forward in reducing some of the challenges that DBAs experience data warehouse maintenance. For example, there is no INDEX command, however, there are certain storage definitions which can make a big difference in the performance of your queries.
We were an early adopter of Amazon Redshift technologies. We’ve seen the following challenges with Redshift deployments, and our team knows all about Amazon Redshift Performance Tuning.
Queries run slower as data grows
As your database grows over time, changes in data no longer match original data distribution style or sort keys settings.
Our experts can address emergency issues to provide you with quick pain relief. We can help your team understand the root causes of performance issues and optimize storage based on your new data. Fixing persistent issues with your data landscape ensures improvement of performance, security, and reliability of your mission-critical data-consuming applications.
Choosing the right strategy
The Redshift optimization project can be considered a regular database migration project with the source and target pointing to different Amazon Redshift clusters. Should you use a copy of the source cluster as a target, or start the optimization project from scratch?
Official Amazon documentation does not recommend using the same cluster for both source and target for your optimization project. Thus, before beginning the optimization process, you need to create a copy of the source cluster. The essence of this method focuses on the creation of a source cluster snapshot followed by its restoration in another cluster.
Running the optimization project, we can choose one of two migration strategies:
Other performance considerations
Sometimes, the Redshift Optimization tool doesn’t always address the problem with specific queries. What other aspects should be considered for performance tuning?
Like most databases, it’s all about understanding how data is stored and how the query optimizer processes the data. Here is a sample of other things to look for that SCT doesn’t address.
Our team can help identify these issues and troubleshoot them to keep your system running with the performance you expect.
Getting started offers
Let our trusted team start with identifying operational risks and provide solutions to mitigate those risks. You can rest assured that our certified professionals, who know everything about cloud database platforms, will boost the performance of your data-consuming applications.
We have a variety of entry level offers to help you tune the performance of your Amazon Redshift storage. Here’s how you can improve the key optimization metrics and increase the queries execution speed.
AWS Database Migration Support
Take advantage of our experienced professionals with deep knowledge of AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT) to migrate your databases to Amazon RDS, Amazon Aurora, and Amazon Redshift.
Future-State Architectural Design
Everyone is talking about the need for a digital transformation, but how do you get there? See how our future-state architecture design can use cutting edge technology to meet your organization’s needs.
Amazon Redshift performance optimization best practices
You can use the Amazon Redshift optimization feature in the AWS Schema Conversion Tool to optimize your Amazon Redshift databases.
This feature looks very interesting and promises to be a very helpful aid to DBAs needing to tune their Redshift. It provides recommendations based on the selection of Distribution Keys and Style, as well as the best choice for the Sort Keys.
Essentially, the Redshift optimization project can be considered a regular AWS SCT migration project with the source and target pointing to Redshift clusters. Here you have to make an important decision: whether to use a copy of the source cluster as a target, or start the optimization project from scratch.
The following video demonstrates the essentials of using the Redshift Optimization to improve the query performance.