--- title: Amazon Redshift Reviews meta_title: 'Amazon Redshift Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 404 reviews by the users' company size, role or industry to find out how Amazon Redshift works for a business like yours. aggregate_rating: rating_value: 4.3 review_count: 404 scale: '5' date_modified: '2026-08-09' parent_category: name: IT Infrastructure url: https://www.g2.com/categories/it-infrastructure --- # Amazon Redshift Reviews **Vendor:** Amazon Web Services (AWS) **Category:** [Data Warehouse Solutions](https://www.g2.com/categories/data-warehouse) **Average Rating:** 4.3/5.0 **Total Reviews:** 404 ## About Amazon Redshift Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that 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 Redshift Pros & Cons **What users like:** - Users value the **fast querying capabilities** of Amazon Redshift, enabling efficient analysis of large datasets seamlessly. (5 reviews) - Users praise the **easy integrations** with other software, enhancing data solutions within the Amazon Redshift ecosystem. (5 reviews) - Users find Amazon Redshift's **ease of use** exceptional, facilitating quick access and efficient data management. (4 reviews) - Users value the **easy integrations** of Amazon Redshift, enhancing their ability to build seamless data solutions. (4 reviews) - Users praise the **impressive speed and scalability** of Amazon Redshift, optimizing data management and query performance. (4 reviews) - Users appreciate the **scalability** of Amazon Redshift, enabling efficient handling of massive data volumes seamlessly. (4 reviews) - Features (3 reviews) - Users value the **efficiency in managing large datasets** with Amazon Redshift, making complex queries seamless and fast. (3 reviews) - Scaling (3 reviews) - Users value the **speed and efficiency** of Amazon Redshift, enhancing their ability to manage large datasets seamlessly. (3 reviews) **What users dislike:** - Users find **feature limitations** in Redshift, especially regarding advanced analytics and multi-language support for coding. (4 reviews) - Users note significant **software limitations** with Redshift, particularly regarding cost and performance issues with complex queries. (4 reviews) - Users find the **complexity of optimizations** in Amazon Redshift burdensome, requiring significant management and maintenance effort. (3 reviews) - Users face **query issues** with Amazon Redshift, requiring extensive optimization and management to maintain performance. (3 reviews) - Users find the **query optimization process cumbersome** , as it requires significant effort and specialized knowledge for efficiency. (3 reviews) - Difficult Management (2 reviews) - Expensive (2 reviews) - Integration Issues (2 reviews) - Learning Difficulty (2 reviews) - Performance Issues (2 reviews) ## Amazon Redshift Reviews ### 1. Powerful Data Warehousing with Speed, but Lacks Out-of-the-Box Optimizations **Rating:** 3.5/5.0 stars **Reviewed by:** Rishav M. | Data Engineer 2, Mid-Market (51-1000 emp.) **Reviewed Date:** October 13, 2025 **What do you like best about Amazon Redshift?** What I like best about Amazon Redshift is its ability to handle massive amounts of data with impressive speed and scalability. It’s designed specifically for data warehousing, so complex queries run efficiently thanks to its columnar storage and massively parallel processing (MPP) architecture. Plus, it integrates smoothly with the AWS ecosystem, making it easier to build end-to-end data solutions accompanied by existing backend infrastructure. **What do you dislike about Amazon Redshift?** In terms of optimizations, there are very little things that come out of the box. A significant amount of effort is required to optimize Redshift. - We have to manage the clusters and nodes since its not a serverless solution (not talking bout spectrum here!) - Concurrency issues when it is being used by a large number of users. We've had to set up limits and checks in place separately, which is a bit annoying. - There's a lot of maintenance overhead. Tasks like vacuuming and analyzing tables to maintain performance still require attention and adds lots of operational complexity. **What problems is Amazon Redshift solving and how is that benefiting you?** In my previous companies, we decided to build out a pandas based reporting solution on top of a data warehouse. We had billions of rows of historical retail data which was ingested into Redshift from our OLTP systems via DMS. We chose Redshift for this since we were already in an AWS environment and it offered easy integrations. - Redshift's columnar nature helped in crunching and aggregating huge data volumes, making it ideal for our reporting solutions. - There are some nice optimizations like sort keys and distribution keys and vacuuming which helps to query the data faster. Though this takes quite some time to set up. - New improvements like Redshift Spectrum also help in querying raw data residing in S3 buckets for adhoc use cases. Overall, I've been satisfied with the product for usecases with small-to medium size data load. ### 2. Reliable and scalable data warehouse with room for improvement **Rating:** 4.5/5.0 stars **Reviewed by:** Kathy L. | Director, Mid-Market (51-1000 emp.) **Reviewed Date:** August 27, 2025 **What do you like best about Amazon Redshift?** Amazon Redshift provides excellent scalability for handling large volumes of structured data and integrates smoothly with other AWS services like S3 and Glue. Query performance is strong for analytical workloads, and the columnar storage significantly speeds up aggregation queries. The ability to separate storage and compute has improved cost management and flexibility, making it easier to scale resources up or down depending on workload needs. **What do you dislike about Amazon Redshift?** While powerful, Redshift can become costly at scale if not carefully monitored and optimized. Query performance sometimes degrades when dealing with complex joins or semi-structured data compared to newer cloud-native solutions. Managing concurrency can also be a challenge, and performance tuning requires specialized knowledge. Additionally, native support for unstructured data is still limited compared to alternatives. **What problems is Amazon Redshift solving and how is that benefiting you?** Amazon Redshift helps consolidate data from multiple sources into a centralized data warehouse, making it easier to run analytical queries at scale. This has allowed our team to generate business insights much faster compared to traditional databases. By leveraging its integration with AWS services like S3 and Glue, we’ve automated our ETL pipelines, reduced manual data preparation, and improved reporting speed. It has also helped optimize decision-making by giving stakeholders near real-time access to dashboards and analytics. ### 3. Easy to scale up and down, cost effective and easy to integrate with EMR and lambda **Rating:** 5.0/5.0 stars **Reviewed by:** Antarix K. | AI Architect, Mid-Market (51-1000 emp.) **Reviewed Date:** October 12, 2025 **What do you like best about Amazon Redshift?** Easy to scale up and down, Multi zone architecture for data safeguarding. Easy to scale schedule. Easy logs access. Easy to setup and simple to inject data using EMR and lambda and Auto Sharing is great help. **What do you dislike about Amazon Redshift?** Query queuing and concurrency issues.At times Auto distribution style does not work wonders and needed to be changed. **What problems is Amazon Redshift solving and how is that benefiting you?** Data ingestion and massaging and manipulation for serving BI reports and ML models to use train on. ## Amazon Redshift Discussions - [Should I use with a data mart for a frontend tool that make request on it ?](https://www.g2.com/discussions/should-i-use-with-a-data-mart-for-a-frontend-tool-that-make-request-on-it) - 3 comments, 3 upvotes - [Is Amazon redshift good for large datasets considering its cost.](https://www.g2.com/discussions/is-amazon-redshift-good-for-large-datasets-considering-its-cost) - 2 comments, 1 upvote - [Is AWS redshift a database?](https://www.g2.com/discussions/is-aws-redshift-a-database) - 1 comment - [When can I use Amazon redshift?](https://www.g2.com/discussions/when-can-i-use-amazon-redshift) - 3 comments - [What are the characteristics of redshift?](https://www.g2.com/discussions/what-are-the-characteristics-of-redshift) - 2 comments - [View Amazon Redshift pricing details and edition comparison](https://www.g2.com/products/amazon-redshift/reviews?filters%5Bsentiment_snippet%5D=1397335&qs=pros-and-cons§ion=pricing&secure%5Bexpires_at%5D=2026-08-14+10%3A52%3A43+-0500&secure%5Bsession_id%5D=92e48f96-5398-4e30-b0ad-34431f5e73d6&secure%5Btoken%5D=fe13f5cddb1e2ad4f6bc48a6d3cbb9f12ad91ed131c63054a80519d74a3a4a9b&format=llm_user) ## Amazon Redshift Integrations - [Fivetran](https://www.g2.com/products/fivetran/reviews) - [Informatica Data Engineering](https://www.g2.com/products/informatica-data-engineering/reviews) - [Informatica Data Integration and Engineering](https://www.g2.com/products/informatica-data-integration-and-engineering/reviews) - [Liquibase](https://www.g2.com/products/liquibase/reviews) - [Metabase](https://www.g2.com/products/metabase/reviews) - [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) - [Microsoft SQL Server](https://www.g2.com/products/microsoft-sql-server/reviews) ## Amazon Redshift Features **Data Management** - Data Integration - Data Compression - Data Quality - Built-In Data Analytics - In-Database Machine Learning - Data Lake Analytics - ETL - Extract Transfer Load - Data Capture and Transfer - Real-Time Analytics - Reporting/Analytics **Storage** - Data Model - Data Types **Integration** - AI/ ML Integration - BI Tool Integration - Data lake Integration **Availability** - Auto Sharding - Auto Recovery - Data Replication **Deployment** - On-Premise - Cloud **Performance** - Integrated Cache **Performance ** - Scalability **Security** - Role-Based Authorization - Authentication - Audit Logs - Encryption **Security** - Data Governance - Data Security **Support** - Multi-Model - Operating Systems **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **Additional Functionality** - Parallel Processing - Ad hoc Analysis - Multiple Data Sources - API - In-Database Processing - Monitoring - Real-Time Reporting - Data Synchronization - Real-Time Monitoring - Data Connectors - Performance Metrics - Ad hoc Reporting - Alerts/Notifications - Access Controls/Permissions - Drag & Drop - Data Visualization - Data Import/Export - Match & Merge - Data Transformation - Secure Data Storage - Data Extraction - AI Copilot - Customizable Reports - Activity Dashboard - Data Migration - In-Memory Processing - Data Mapping ## Top Amazon Redshift Alternatives - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,145 reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - 4.6/5.0 (714 reviews) - [Rocket Vertica](https://www.g2.com/products/rocket-vertica/reviews) - 4.3/5.0 (195 reviews)