In today's modern world, Big Data and Data Analytics are some of the most popular on-demand technologies in use by many companies. They looked like innovations in the past, but today they are among the most needed tools to serve millions of customers.
Within this, one of the most famous and notable data warehouses is Amazon Redshift which, in short, is a cloud-based big data storage solution offered by Amazon Web Services (AWS). It allows companies to store petabytes of data in easily accessible “clusters” that can be queried in parallel.
In this article, you will understand why Amazon Redshift is great for companies looking for technological scalability with costs under control. Follow up!
About Amazon Redshift
Amazon Redshift is a fully managed, large-scale data warehouse offered as a cloud service by Amazon.
Fully managed in this context means that the end user is spared all the activities related to hosting, maintaining and ensuring the reliability of an always-running data warehouse.
Amazon Redshift offers a Postgres-compatible query layer and is compatible with most commonly used SQL-based tools and data intelligence applications.
In addition to the data warehouse service, AWS also offers another service called Redshift Spectrum, which is for executing SQL queries on S3 data — this service is not covered here as it is a fundamentally different concept.
When contemplating using a managed third-party service like the backbone data warehouse, the first point of contention for a data architect would be the foundation on which the service is built, especially as the foundation has a critical impact on how the service is built. will behave in various circumstances.
In short, Amazon Redshift is designed for big data and can easily scale thanks to its modular node design. With its multi-tiered structure, it allows multiple queries to be processed simultaneously, reducing wait times.
About Amazon Redshift Scalability
One of the most critical factors that makes a fully managed data warehouse service valuable is its ability to scale. In this sense, Amazon Redshift can scale quickly and customers can choose the extent of capacity according to their peak workload hours.
It supports two types of scaling operations:
- Classic resizing: the first is classic resizing, which allows clients to add nodes in a matter of hours. Classic resizing is available for all node types.
- Elastic resizing: elastic resizing enables even faster scaling operations, but is only available for nodes other than the DC1 node type. That said, there is a small window of time during the elastic resize operation where the database will be unavailable for querying.
Redshift also lets you rotate a cluster by quickly restoring data from a snapshot. This is very useful when customers need to add compute resources to support high concurrency.
→ Also read: Implementing Amazon Redshift on Autoglass!
How about, can we show you what Redshift is and how it works? talk to us right now for more details, and see how we can help you implement this solution in your company!
