The size of data to be analyzed is becoming huge and massive day by day with the applications gaining adhesion. Some problems such as unmanageable data size and queries taking a lot of time are sure to be encountered. Here comes the need for a competent data warehousing solution for data storage that will assist with keeping your data organized as well as making it easily accessible for analytics and reporting.
Amazon Redshift is a cloud-based, petabyte-scale data warehouse service that is provided and fully managed by Amazon Web Services (AWS). It is a solution that is well efficient and effective to collect and store all your data. You can analyze it by making use of various business intelligence tools available out there to gain insights for your customers and business.
Below listed are a few of the merits or advantages of Amazon Redshift. Let’s dive into them one by one:
Amazon Redshift is horizontally scalable. Scalability is a very mandatory feature for any Data Warehousing solution and activities. We just need to append or add extra nodes using Cluster API or AWS Console, whenever there is a requirement of high storage or speed. The application, though, stays uninterrupted during this process, as the existing cluster remains available for the read operations. The transition process here is quite smooth and flexible as data is moved parallelly between nodes of old and new clusters.
Several factors are adding up to the high performance of Redshift such as query optimization, efficient data compression, and parallelism. A huge and repetitive type of data is stored in the columnar storage database. This further leads to a decrease of I/O operations on disk which increases the performance.
There are many security features inbuilt with Amazon Redshift. Data Encryption, VPC for network isolation, various ways to access control options are available. Cluster Encryption can be enabled at the time of launching the cluster to encrypt data stored in the cluster. Server-side encryption and client-side encryption can be used when loading data from S3.
Redshift offers a petabyte range of data storage. We can choose Dense Storage type of compute nodes that offer large storage space. You can add more nodes to your cluster to exceed it beyond the petabyte range.
Redshift Query Engine is similar to the interface as PostgreSQL, which is based on ParAccel. It is also readily compatible with Postgres JDBC/ODBC Drivers.
Redshift is considerably cheap than other on-premise alternative solutions prevalent. We are flexible to opt whether we can choose the expense as a capital expense or operational expense.
There are various use cases where Amazon Redshift is being applied in the industry. Let’s look up to some live examples:
Amazon Redshift has been used for gathering together structured data from the data warehouse and semi-structured data from application logs so that we can acquire real-time insights on applications and systems.
We can build extremely amazing and powerful reports and dashboards using existing business intelligence tools. This proves quite simple and cost-effective to run high-performance queries on huge petabytes of structured data.
Expedia has been using this a standard deployment model to develop and deploy applications faster, troubleshoot problems as well as scale to process large volumes of data.
Data Sitting which takes place into Redshift feeds into time-sensitive apps. This is mainly responsible for the database to remain active, otherwise, it would adversely affect the business.
Some of the benefits offered here are, the maximum amount of fidelity is ensured with no information lost. Slicing and Dicing can be possible in any dimension.
Redshift offers analytics in a SaaS model to its customers. The mentioned enterprises proactively use Redshift to deploy machine-learning models, mission-critical applications, business-critical SAP applications, and identification of cyber-security threats.
SNDK Corp has devised Amazon Redshift, which is an excellent solution when it comes to data warehousing. It has many benefits over other alternatives such as Snowflake and Bigquery. It has cut down the cost of running a data warehouse, as it is cheap and allows storing entry-level data. Above are the use cases discussed which include data-driven services creating new revenue streams for companies.
In this conclusion, we will summarize some features of Amazon Redshift in a nutshell. It is extremely scalable and provides high performance. It is secure and easy to manage. Some of the readily available management points include automated backups, fault tolerance, and integration with third-party tools. Some of the security features encountered are network isolation, end-to-end encryption, and audit and compliance.
Also published on: https://www.sndkcorp.com/amazon-redshift-introduction/