Amazon rds vs Redshift

Introduction to Amazon rds vs Redshift

Amazon rds is a relational database service which is provided by Amazon web services, it supports to store and organize data of the database engine and helps to manage tasks of the database, it operates and scales the relational database in the cloud, it brings up the database in an easy way without worrying about the infrastructure, whereas the Amazon Redshift is a cloud-based service or a data warehouse service that is used for collecting and storing data, also it enables a user to analyze the data using Business Intelligence tools and simplifies the process of handling large scale data sets.

Head to Head Comparison Between Amazon rds vs Redshift (Infographics)

Below are the top 10 differences between Amazon rds vs Redshift:

Comparison Table of Amazon rds vs Redshift

S.N	Amazon rds	Redshift
1.	The Amazon rds is a web service in the cloud.	Whereas, it is a petabyte-scale data warehouse service in the cloud.
2.	It is a relational database service.	Whereas, the Redshift is a non-relational database.
3.	It works fine for OLTP (Online Transactional Processing) system which gives instant results with fewer data.	And, it works for OLAP (Online Analytical Processing) system, so that the analytical and reporting workload is heavy and it interferes with the OLTP database.
4.	The data volume is in terabytes, and it has 64 terabytes storage limit.	Where its data volume is in petabytes, it has unlimited data storage.
5.	The cost of rds is less but we wanted to pay only for the resources which we would be consuming.	Whereas, the costs of Redshift are also less to operate than any other cloud data warehouse.
6.	It is secure so by using Amazon rds we can easily control the network for accessing our database, and also we get the option for isolating the database instances.	On the other hand, we can create our own security groups and can attach to cluster, so that we can design our security parameters as per the requirements.
7.	It is flexible, hence we can able to scale the computing resources or we can scale the storage capacity which is associated with the database.	It is also flexible but it allows removing the cluster, creating a cluster, deleting the cluster, also to take a snapshot of it, and move that snapshot to a different region.
8.	Its database engine includes MySQL, SQL Server, Oracle database, Maria database, Amazon Aurora, and PostgreSQL.	Whereas the redshift uses adapted PostgreSQL as the database engine.
9.	It has 64vCPU and 244GB RAM computing resources.	Whereas, redshift computing resources include nodes with vCPU and 244 GN RAM.
10.	The data storage of rds is 6 terabytes.	On the other hand, it has 16 terabytes per Amazon Redshift instance.

Key Differences of Amazon rds vs Redshift

Scalability:

When we have a choice to select different databases then the most important is to check the scalability of it, both rds and redshift allow us to scale the database as per the requirement.
The scaling of rds is based on the virtual instances and that is done by reconfiguring the capability of virtual instances, the scaling of rds can take few minutes and it can be done in few clicks in the console of AWS, whereas the architecture of redshift is complex it means the scaling is not as seamless as it is in rds. The resizing of instances can be done in few minutes because it supports elastic resize, the database unavailable time window is higher than that rds, it means seeing the storage capacity of scaling redshift is higher so that the unlimited number of users can access it.

Performance:

The performance of both the databases depends on the key distribution mechanism where the rds has sharding capability with carefully designed keys in which customers can get more performance, whereas the redshift has the option of SORT key and DIST key, when that is used correctly then the performance in joins and complex queries will improve, redshift is a fastest performing data warehouse on the computing platform.

Maintenance:

The maintenance of rds is low than redshift because it has a simple architecture, also it has automated tasks so that it does not have more things to maintain by end-user. The administrative task in redshift which needs to be executed manually by the administrator of the cluster, that uses a delete marker for ‘DELETE’ and ‘UPDATE’ queries, it means the archival process is necessary for actual deletion and this process is to be done by using ‘VACUUM’ command, whereas, redshift also has an ‘ANALYZE’ command to ensure all metadata and tables are kept updated.

Data Structure:

Basically, the structure of the rds is row-oriented and it stores the data, on the other hand, redshift has a columnar structure so that it optimized fast retrieval of columns. The rds querying is depended on the engine used and redshift uses Postgres standard. When that comes to a unique constraint in the insertion key then redshift does not do a good job and it is expected that the end-user will manage it themselves, whereas the rds supports unique key constraints in the database engine.

Pricing:

The pricing of the rds and redshift is including the storage and compute, and they are allowed to pay only as per the use. The price for rds is low because it is simple and it has lower scaling capabilities, it starts at 0.17$ per hour for MySQL, Postgres, Maria DB which is very low and if the customer wants to use the existing oracle database then AWS also has a policy for Oracle in lower rates, whereas the price for redshift is more with the lowest current generation, its starting price is .25$ per hour and it is highly available service. When the customer uses multiple nodes then the price increases with the number of nodes.

Conclusion

In this article, we conclude that the RDS and the Redshift both are having attractive use cases, we can think on behalf of them by scaling it, by operating it, and using those as per our requirements, and both the services will work fine individually, we cannot make a choice between them.

Recommended Articles

This is a guide to Amazon rds vs Redshift. Here we discuss key differences with infographics and comparison tables, respectively. You may also have a look at the following articles to learn more –

1. Hadoop vs Redshift
2. Hadoop vs Splunk
3. Amazon SQS
4. Amazon Alternatives