Amazon Relational Database Service (RDS) vs. Amazon Redshift

If your application needs a relational data store and uses other AWS services, AWS RDS is a no-brainer. It offers all the traditional database features, makes it a snap to set up, creates cross-region replication, has advanced security, built-in monitoring, and much more at a very good price. You can also set up streaming to a data lake using various other AWS services on your RDS.

Incentivized

If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)

Incentivized

• Automated Database Management: We use it for streamlining routine tasks like software patching and database backups.
• Scalability on Demand: we use it to handle traffic spikes, scaling both vertically and horizontally.
• Database Engine Compatibility: It works amazingly with multiple database engines used by different departments within our organization including MySQL, PostgreSQL, SQL Server, and Oracle.
• Monitoring: It covers our extensive monitoring and logging, and also has great compatibility with Amazon CloudWatch

Incentivized

• Redshift is fully managed. Small teams do not have the resources to maintain a cluster. CloudWatch metrics are provided out-of-the-box, and it is easy to configure alarms.
• Redshift's console allows you to easily inspect and manage queries, and manage the performance of the cluster.
• Redshift is ubiquitous; many products (e.g., ETL services) integrate with it out-of-the-box.
• Writing .csvs to S3 and querying them through Redshift Spectrum is convenient.

Incentivized

• It is a little difficult to configure and connect to an RDS instance. The integration with ECS can be made more seamless.
• Exploring features within RDS is not very easy and intuitive. Either a human friendly documentation should be added or the User Interface be made intuitive so that people can explore and find features on their own.
• There should be tools to analyze cost and minimize it according to the usage.

Incentivized

• It could benefit from adding data integrity and programming tools common to other database management systems.
• Amazon Redshift is based on PostgreSQL 8.0.2. That version of PostgreSQL was released in December 2006. While PostgreSQL was much improved since then, the new features were not implemented in Redshift. Many basic features are missing from it.
• Primary keys can be declared but not enforced. Referential integrity (foreign keys) can be declared but not enforced. UNIQUE and CHECK constraints are not supported and cannot be declared.
• IDENTITY can be declared on a column, and Redshift will put unique values into it. However: IDENTITY values in the newly inserted rows won’t be incremental or sequential. To implement a sequential number, you need to write your own custom code.
• There are no stored procedures in Redshift. We are writing SQL script files, and then parsing and running them one statement at a time from a Python program. This also enabled us to implement execution-time error logging.
• In SQL scripts, to check for the row count of affected rows, a complicated join query against some system tables or views has to be executed.
• Data Control Language (DCL) does not exist. No statements like IF, WHILE, DO, RAISERROR, etc.
• On performance of views… Views do not “pass-through” a query parameter which is a potential problem for performance.
• When selecting against a view with the WHERE clause outside of the view, the inner query of the view will be executed first without consideration for the WHERE clause, and only then the WHERE clause will be applied.
• Certain clauses of SQL work many times faster than other clauses. So be careful and test your statements for performance earlier rather than later, especially if working with a large data set.
• There was a situation when DELETE FROM JOIN was unacceptably slow. Replacing JOIN with the USING clause made DELETE instantaneous.

Incentivized

We do renew our use of Amazon Relational Database Service. We don't have any problems faced with RDS in place. RDS has taken away lot of overhead of hosting database, managing the database and keeping a team just to manage database. Even the backup, security and recovery another overhead that has been taken away by RDS. So, we will keep on using RDS.

Incentivized

I've been using AWS Relational Database Services in several projects in different environments and from the AWS products, maybe this one together to EC2 are my favourite. They deliver what they promise. Reliable, fast, easy and with a fair price (in comparison to commercial products which have obscure license agreements).

Incentivized

Overall it serves all our aspects of data management like data cleaning, data manipulation, and data reporting on the cloud platform. We can create stored procedures and triggers in it very easily as all the options are self suggested in it. We can easily attach the results of ARS to the other tools as well for drawing the statistical results.

Incentivized

I have only had good experiences in working with AWS support. I will admit that my experience comes from the benefit of having a premium tier of support but even working with free-tier accounts I have not had problems getting help with AWS products when needed. And most often, the docs do a pretty good job of explaining how to operate a service so a quick spin through the docs has been useful in solving problems.

Incentivized

The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support

Incentivized

the online training & digital content available on the web from AWS was having sufficient information to deploy and run the service

Incentivized

Amazon Relational Database Service (RDS) stands out among similar products due to its seamless integration with other AWS services, automated backups, and multi-AZ deployments for high availability. Its support for various database engines, such as MySQL, PostgreSQL, and Oracle, provides flexibility. Additionally, RDS offers managed security features, including encryption and IAM integration, enhancing data protection. The pay-as-you-go pricing model makes it cost-effective. Overall, Amazon RDS excels in ease of use, scalability, and a comprehensive feature set, making it a top choice for organizations seeking a reliable and scalable managed relational database service in the cloud.

We evaluated [Amazon] Redshift vs BigQuery vs Amazon EMR, back in 2014. Back then BigQuery cost was slightly higher than that of [Amazon] Redshift price structure. Amazon EMR, needs lots more management (Admin tasks) and EMR is designed to be ephemeral and not designed to be a data store. [Amazon] Redshift was ideal with the price structure, performance and ROI[.]

Incentivized

• The overall cost increases, but we spect this and we can mitigate other risks.
• Is easy to work from the cloud. Is reliable, but we keep our local solution as well where RDS works quite good.
• RDS allow us to focurs on owr objetives instead of the other matters regarding databases.

Incentivized

• It allows for an almost seamless integration of our data which can then be used by other departments for analytical purposes.
• No in house resources are needed for keeping the data alive and performing backup/migration tasks of the data in its end state.

Incentivized