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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon RDS vs Amazon Redshift

Amazon RDS vs Amazon Redshift

OverviewDecisionsComparisonAlternatives

Overview

Amazon RDS
Amazon RDS
Stacks16.2K
Followers10.8K
Votes761
Amazon Redshift
Amazon Redshift
Stacks1.5K
Followers1.4K
Votes108

Amazon RDS vs Amazon Redshift: What are the differences?

Introduction: Here we will explore the key differences between Amazon RDS and Amazon Redshift.

  1. Database Purpose: Amazon RDS is a relational database service designed for OLTP workloads, offering support for various database engines such as MySQL, PostgreSQL, SQL Server, etc. On the other hand, Amazon Redshift is a data warehousing service ideal for OLAP workloads, specifically optimized for analyzing large datasets.

  2. Data Scaling: Amazon RDS allows for vertical scaling, meaning you can resize your database instance, but there are limits to how much you can scale vertically. In contrast, Amazon Redshift enables horizontal scaling by adding nodes to the data warehouse cluster, providing superior scalability for handling massive amounts of data.

  3. Query Performance: Amazon RDS is optimized for transactional processing and may not perform as efficiently for complex analytical queries on large datasets. Amazon Redshift, being a cloud-based data warehouse, is specifically designed to offer fast query performance for analytical workloads, including complex joins and aggregations.

  4. Pricing Model: Amazon RDS charges based on the instance type, storage, and data transferred. In contrast, Amazon Redshift pricing is based on a combination of the type and number of nodes in the cluster, along with the amount of data stored, providing more flexibility for cost optimization depending on usage patterns.

  5. Backup and Restore: Amazon RDS provides automated backups and restores, allowing you to recover your database to any point in time within the retention period. With Amazon Redshift, you can take snapshots of your data warehouse at specific points in time and restore them, but the process is more geared towards creating and restoring full cluster backups.

  6. Concurrency: Amazon RDS is suited for handling multiple concurrent connections typical in OLTP applications. Amazon Redshift, being optimized for analytics, can efficiently handle multiple queries running in parallel and support high levels of concurrency for complex analytical workloads.

In Summary, Amazon RDS is ideal for OLTP workloads with relational database needs, while Amazon Redshift is tailored for OLAP workloads with a focus on analytical processing and scalability.

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Advice on Amazon RDS, Amazon Redshift

datocrats-org
datocrats-org

Jul 29, 2020

Needs adviceonAmazon EC2Amazon EC2TableauTableauPowerBIPowerBI

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.

319k views319k
Comments

Detailed Comparison

Amazon RDS
Amazon RDS
Amazon Redshift
Amazon Redshift

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.

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.

Pre-configured Parameters;Monitoring and Metrics;Automatic Software Patching;Automated Backups;DB Snapshots;DB Event Notifications;Multi-Availability Zone (Multi-AZ) Deployments;Provisioned IOPS;Push-Button Scaling;Automatic Host Replacement;Replication;Isolation and Security
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.;Fault Tolerant- Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3.;SQL - Amazon Redshift is a SQL data warehouse and uses industry standard ODBC and JDBC connections and Postgres drivers.;Isolation - Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster.;Encryption – With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware-acccelerated AES-256 encryption for data at rest.<br>
Statistics
Stacks
16.2K
Stacks
1.5K
Followers
10.8K
Followers
1.4K
Votes
761
Votes
108
Pros & Cons
Pros
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
Pros
  • 41
    Data Warehousing
  • 27
    Scalable
  • 17
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
Integrations
No integrations available
SQLite
SQLite
MySQL
MySQL
Oracle PL/SQL
Oracle PL/SQL

What are some alternatives to Amazon RDS, Amazon Redshift?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon Aurora

Amazon Aurora

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Google Cloud SQL

Google Cloud SQL

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

ClearDB

ClearDB

ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Azure SQL Database

Azure SQL Database

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

Stitch

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

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