Data warehouses are no longer new concepts for businesses taking a plunge into digitization. Over time, more and more businesses have switched from legacy platforms to cloud-based solutions that provide them with greater flexibility and scalability. In 2022, almost every business process carried out across all major industries is data-driven. Right from understanding the needs of your customers to assessing the profitability of your business, you need to store, manage, track, and share data.
This is why the importance of data warehouses like Amazon Redshift is increasing steadily.
Amazon Redshift is a highly sought-after data warehouse that allows businesses to store and analyze their datasets on a centralized platform to obtain important business insights. The data warehouse helps users extract data from multiple platforms, transform the same into a common format, and analyze it for making assessments that matter. It is a fully-managed data warehouse by Amazon offered as a cloud service to organizations across the world.
When we say that Amazon Redshift is fully-managed, it means that it relieves users from performing a range of tedious activities revolving around data maintenance, hosting, and making sure that the data warehouse keeps running. The cloud-based data warehouse is compatible with several SQL-based tools and data intelligence applications commonly implemented by organizations across the board.
If you are planning to move to the cloud for seamless data management using Amazon Redshift, here are some of the most noteworthy features of the data warehouse:
Distributed Design Approach (MPP)
Amazon Redshift makes use of a distributed design approach called Massively Parallel Processing (MPP). MPP involves multiple processors applying a “divide and rule” to bigger data jobs. Here, a bigger processing job gets segregated into smaller jobs in an organized way. These jobs are then distributed between a cluster of processors called compute nodes.
Instead of working sequentially, these processors finish their computations simultaneously. This allows Amazon Redshift to reduce the amount of time taken to complete a massive job to a great extent.
Column-based Orientation Of Data
While managing your datasets, you can organize the data in columns or rows, determined by the nature of your workflow. In most cases, data is organized in different rows. This is because raw-oriented platforms allow users to undertake a large number of small processes at a faster rate. This approach, also known as Online Transaction Processing (OLTP), is used by many operational databases on a regular basis.
On the other hand, the column-based orientation of data provides you with higher speed while accessing large volumes of data. This is the approach followed by Amazon Redshift for managing your database. In an Online Analytical Processing (OLAP) environment like Redshift, users normally apply smaller queries to larger datasets. In such a situation, being a column-oriented database helps Amazon Redshift complete large-scale data processing jobs without any unnecessary delays.
Data Encryption
When it comes to storing and managing data stored in the cloud, it is always important to ensure complete privacy and security of data. Especially for organizations operating in sectors like healthcare, finance, and law, the smallest breach of security can have long-term implications.
Amazon Redshift makes sure that your valuable data is protected at all times through end-to-end data encryption. This allows users to adhere to major data compliance regulations like GDPR, CCPA, HIPAA, and more.
Redshift provides users with data encryption options that are powerful and customizable. These options have been kept flexible to allow users to choose the standards that best suit their needs. By getting rid of the conventional “one size fits all” approach, Amazon Redshift provides more freedom and personalization to users when it comes to keeping their datasets secure.
Here are a few important characteristics of the data encryption features offered by Amazon Redshift:
- The data warehouse allows users to migrate data between unencrypted and encrypted clusters as per their requirements
- It provides users with the option of employing a customer-managed or AWS-managed key
- It allows users to choose between AWS Key Management Service and the Hardware Security Module (HSM)
- According to the scenarios faced by users, they are allowed to choose single or double data encryption
Seamless Fault Tolerance
Fault tolerance, as the name suggests, refers to the ability of a system to keep operating effectively even after the failure of a few components. In the case of data warehouses, fault tolerance allows you to see how capable a job is to keep running even when a few clusters or processors have gone offline.
Amazon Web Services (AWS) is known for tracking and monitoring its clusters on a 24/7 basis. Whenever the nodes, clusters, or drives fail, Amazon Redshift re-replicates your data and shift it to healthier nodes automatically. This would prevent the system from experiencing serious issues and keep your operations intact.
Provision For Network Isolation
If you are looking for additional security for your business data, Amazon Redshift allows you to isolate your network with the data warehouse. By doing so, you can restrict the network access to the clusters of your organization by enabling the Amazon Virtual Private Cloud (VPC). This would keep your data warehouse connected to your existing IT infrastructure along with the privacy of IPsec VPN.
Concurrency Limits
Concurrency limits help users ascertain the maximum number of clusters or nodes they are able to provision at a specific point in time. With these limits, you can ensure that all users have adequate computing resources at their disposal. Amazon Redshift helps users democratize the cloud-based data warehouse through concurrency limits.
While the concurrency limits maintained by Redshift are similar to most data warehouses, it provides users with a little extra flexibility. Moreover, it configures these limits on the basis of different regions instead of applying one limit to every user.
The Final Word
These were some noteworthy features of Amazon Redshift to keep in mind before switching to the cloud-based data warehouse. With the flexibility of the cloud and the credibility of AWS, Redshift ensures that you are able to manage your valuable datasets in a smooth and sustainable manner.