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Amazon RDS

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Amazon RDS vs Amazon Redshift: What are the differences?

Amazon RDS: Set up, operate, and scale a relational database in the cloud. Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call; Amazon Redshift: Fast, fully managed, petabyte-scale data warehouse service. Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Amazon RDS can be classified as a tool in the "SQL Database as a Service" category, while Amazon Redshift is grouped under "Big Data as a Service".

Some of the features offered by Amazon RDS are:

  • Pre-configured Parameters
  • Monitoring and Metrics
  • Automatic Software Patching

On the other hand, Amazon Redshift provides the following key features:

  • Optimized for Data Warehousing- It uses columnar storage, data compression, and zone maps to reduce the amount of IO needed to perform queries. Redshift has a massively parallel processing (MPP) architecture, parallelizing and distributing SQL operations to take advantage of all available resources.
  • Scalable- With a few clicks of the AWS Management Console or a simple API call, you can easily scale the number of nodes in your data warehouse up or down as your performance or capacity needs change.
  • No Up-Front Costs- You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing.

"Reliable failovers" is the primary reason why developers consider Amazon RDS over the competitors, whereas "Data Warehousing" was stated as the key factor in picking Amazon Redshift.

Airbnb, Netflix, and Coursera are some of the popular companies that use Amazon RDS, whereas Amazon Redshift is used by Lyft, Coursera, and 9GAG. Amazon RDS has a broader approval, being mentioned in 1437 company stacks & 526 developers stacks; compared to Amazon Redshift, which is listed in 270 company stacks and 68 developer stacks.

Advice on Amazon RDS and Amazon Redshift

We need to perform ETL from several databases into a data warehouse or data lake. We want to

  • keep raw and transformed data available to users to draft their own queries efficiently
  • give users the ability to give custom permissions and SSO
  • move between open-source on-premises development and cloud-based production environments

We want to use inexpensive Amazon EC2 instances only on medium-sized data set 16GB to 32GB feeding into Tableau Server or PowerBI for reporting and data analysis purposes.

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Replies (3)

You could also use AWS Lambda and use Cloudwatch event schedule if you know when the function should be triggered. The benefit is that you could use any language and use the respective database client.

But if you orchestrate ETLs then it makes sense to use Apache Airflow. This requires Python knowledge.

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Recommends
Airflow

Though we have always built something custom, Apache airflow (https://airflow.apache.org/) stood out as a key contender/alternative when it comes to open sources. On the commercial offering, Amazon Redshift combined with Amazon Kinesis (for complex manipulations) is great for BI, though Redshift as such is expensive.

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Recommends

You may want to look into a Data Virtualization product called Conduit. It connects to disparate data sources in AWS, on prem, Azure, GCP, and exposes them as a single unified Spark SQL view to PowerBI (direct query) or Tableau. Allows auto query and caching policies to enhance query speeds and experience. Has a GPU query engine and optimized Spark for fallback. Can be deployed on your AWS VM or on prem, scales up and out. Sounds like the ideal solution to your needs.

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Pros of Amazon RDS
Pros of Amazon Redshift
  • 163
    Reliable failovers
  • 154
    Automated backups
  • 129
    Backed by amazon
  • 92
    Db snapshots
  • 86
    Multi-availability
  • 29
    Control iops, fast restore to point of time
  • 27
    Security
  • 23
    Elastic
  • 20
    Automatic software patching
  • 20
    Push-button scaling
  • 4
    Replication
  • 3
    Reliable
  • 2
    Isolation
  • 37
    Data Warehousing
  • 27
    Scalable
  • 16
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
  • 1
    Cheap and reliable
  • 1
    Isolation
  • 1
    Best Cloud DW Performance
  • 1
    Fast columnar storage

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What is Amazon RDS?

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

What is Amazon Redshift?

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Amazon RDS?
What companies use Amazon Redshift?
See which teams inside your own company are using Amazon RDS or Amazon Redshift.
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What tools integrate with Amazon Redshift?

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Jul 9 2019 at 7:22PM

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What are some alternatives to Amazon RDS and Amazon Redshift?
Apache Aurora
Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
Heroku Postgres
Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
Google Cloud SQL
MySQL databases deployed in the cloud without a fuss. Google Cloud Platform provides you with powerful databases that run fast, don’t run out of space and give your application the redundant, reliable storage it needs.
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How developers use Amazon RDS and Amazon Redshift
Pathwright uses
Amazon RDS

While we initially started off running our own Postgres cluster, we evaluated RDS and found it to be an excellent fit for us.

The failovers, manual scaling, replication, Postgres upgrades, and pretty much everything else has been super smooth and reliable.

We'll probably need something a little more complex in the future, but RDS performs admirably for now.

AngeloR uses
Amazon RDS

We are using RDS for managing PostgreSQL and legacy MSSQL databases.

Unfortunately while RDS works great for managing the PostgreSQL systems, MSSQL is very much a second class citizen and they don't offer very much capability. Infact, in order to upgrade instance storage for MSSQL we actually have to spin up a new cluster and migrate the data over.

Olo uses
Amazon Redshift

Aggressive archiving of historical data to keep the production database as small as possible. Using our in-house soon-to-be-open-sourced ETL library, SharpShifter.

Wirkn Inc. uses
Amazon RDS

Our PostgreSQL servers, where we keep the bulk of Wirkn data, are hosted on the fantastically easy and reliable AWS RDS platform.

Digital2Go uses
Amazon RDS

We use Aurora for our OLTP database, it provides significant speed increases on top of MySQL without the need to manage it

fadingdust uses
Amazon RDS

RDS allows us to replicate the development databases locally as well as making it available to CircleCI.

Christian Moeller uses
Amazon Redshift

Connected to BI (Pentaho)

Kovid Rathee uses
Amazon Redshift

OLAP and BI