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Amazon Redshift pros and cons

Vendor: Amazon Web Services (AWS)

3.9 out of 5

72 reviews
87% willing to recommend

Pros & Cons summary

Amazon Redshift offers strong performance, data compression, and scalability for significant data handling. Integration with AWS services like S3 enhances data management, while advanced analytics and query efficiencies suit large datasets. Competitive pricing and easy setup boost its appeal. However, query compilation time and handling unstructured data need improvement. Multibyte character set migration and integration costs present challenges, along with concerns about node stability.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Amazon Redshift offers exceptional performance, scalability, and data compression capabilities, making it ideal for handling large datasets and complex queries.

The ability to integrate seamlessly with other AWS services and tools is a significant advantage, allowing users to leverage the entire AWS ecosystem effortlessly.

Machine learning capabilities and real-time analytics features in Amazon Redshift enable on-the-fly data analysis, adding value to data warehousing and business intelligence applications.

Amazon Redshift provides easy data migration from other databases, supported by dedicated migration tools that facilitate smooth transitions and automatic script conversion.

With its flexible and efficient data management abilities, Amazon Redshift supports parallel processing and can handle extensive data volumes, offering robust cluster and spectrum features.

CONS

Amazon Redshift's query compilation time requires significant improvement, particularly for dynamically generated queries.

Data migration challenges may arise, especially when dealing with multibyte character sets, and handling unstructured data has been found to be cumbersome and slow.

The pricing structure of Amazon Redshift is considered high compared to competitors, with customer support also cited for being costly and less responsive.

Handling concurrent queries results in poor performance, and there is a need for enhanced flexibility in processing different data formats effectively.

Amazon Redshift lacks features like a pivot function, cloning capabilities, and more comprehensive integration with non-AWS services, making it less competitive in certain scenarios.

Amazon Redshift Pros review quotes

Full Stack Engineer at a tech services company with 11-50 employees

Jun 22, 2017

The valuable features are performance, data compression, and scalability.

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NW

BI Manager at jfrog

Jun 27, 2017

You can copy JSON to the column and have it analyzed using simple functions.

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Manager Data Services at a logistics company with 201-500 employees

Jul 17, 2017

Easy to build out our snowflake design and load data.

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Amazon Redshift

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Senior Solutions Engineer, West at a tech vendor with 5,001-10,000 employees

Jul 19, 2017

Redshift COPY command, because much of my work involved helping customers migrate large amounts of data into Redshift.

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Principal Consultant at Inawisdom

May 9, 2018

The ability to reload data multiple times at different times.

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NW

BI Manager at jfrog

Feb 4, 2019

It allows you write complex queries and perform row by row processes.

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Mediha Šiljić

Lead Data Engineer at Sensilab

Jul 31, 2019

The most valuable features are that it's easy to set up and easy to connect the many tools that connect to it.

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reviewer1207005

Head of Analytics at a tech services company with 10,001+ employees

Oct 13, 2019

The solution's flexibility is its most valuable feature. It's also easy to scale and has relatively painless pricing.

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reviewer1221354

Senior Software Engineer at a tech services company with 51-200 employees

Nov 7, 2019

The initial setup of this solution is straightforward.

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MiodragMilojevic

Senior Data Archirect at Telenor

Nov 27, 2019

The product is relatively easy to use because there is no indexing and no partitions.

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Amazon Redshift Cons review quotes

Full Stack Engineer at a tech services company with 11-50 employees

Jun 22, 2017

Query compilation time needs a lot of improvement for cases where you are generating queries dynamically.

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NW

BI Manager at jfrog

Jun 27, 2017

It lacks a few features which can be very useful, such as stored procedures

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Manager Data Services at a logistics company with 201-500 employees

Jul 17, 2017

It would be nice if we could turn off an instance. However, it would retain the instance in history, thus allowing us to restart without beginning from scratch.

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Amazon Redshift

Free Report: Amazon Redshift Reviews and More

Learn what your peers think about Amazon Redshift. Get advice and tips from experienced pros sharing their opinions. Updated: December 2025.

879,259 professionals have used our research since 2012.

Senior Solutions Engineer, West at a tech vendor with 5,001-10,000 employees

Jul 19, 2017

Migrating data from other data sources can be challenging when you are working with multibyte character sets.

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Principal Consultant at Inawisdom

May 9, 2018

Should be made available across zones, like other Multi-AZ solutions.

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NW

BI Manager at jfrog

Feb 4, 2019

In the next release, a pivot function would be a big help. It could save a lot of time creating a query or process to handle operations.

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Mediha Šiljić

Lead Data Engineer at Sensilab

Jul 31, 2019

Compatibility with other products, for example, Microsoft and Google, is a bit difficult because each one of them wants to be isolated with their solutions.

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reviewer1207005

Head of Analytics at a tech services company with 10,001+ employees

Oct 13, 2019

The speed of the solution and its portability needs improvement.

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reviewer1221354

Senior Software Engineer at a tech services company with 51-200 employees

Nov 7, 2019

Running parallel queries results in poor performance and this needs to be improved.

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MiodragMilojevic

Senior Data Archirect at Telenor

Nov 27, 2019

The product could be improved by making it more flexible.

Read full review

Show 10 more reviews (out of 63)

Product Categories

Product Categories

Cloud Data Warehouse

Database Management Systems (DBMS)

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Product Categories

Product Categories

Cloud Data Warehouse

Database Management Systems (DBMS)

Popular Comparisons

Popular Comparisons

Azure Data Factory vs Amazon Redshift

Teradata vs Amazon Redshift

Snowflake vs Amazon Redshift

Oracle Exadata vs Amazon Redshift

OpenText Analytics Database (Vertica) vs Amazon Redshift

Dremio vs Amazon Redshift

VMware Tanzu Data Solutions vs Amazon Redshift

Microsoft Azure Synapse Analytics vs Amazon Redshift

IBM Netezza Performance Server vs Amazon Redshift

Oracle Autonomous Data Warehouse vs Amazon Redshift

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SAP BW4HANA vs Amazon Redshift

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