Amazon Redshift vs Dremio comparison

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Amazon Redshift

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Executive SummaryUpdated on Feb 15, 2026

Amazon Redshift and Dremio both compete in the data management platform category. Amazon Redshift has an advantage in handling petabyte-scale data with high performance through Massively Parallel Processing, while Dremio excels in data integration and governance features.

Features: Amazon Redshift's scalability is highlighted by its ability to manage petabyte-scale data and support multiple file formats, enhancing its versatility for large-scale operations. It also benefits from Massively Parallel Processing for high-performance data handling. Dremio distinguishes itself by providing a unified data access and virtualization pane, efficient data source integration, and strong data lineage and transformation tools vital for governance and compliance.

Room for Improvement: Amazon Redshift could improve in snapshot restoration times, AWS IAM integration, and query optimizations. Notable issues include challenges with vacuum processes and data migrations. Dremio faces difficulties with its Delta connector support and needs to enhance large query execution speed. Users have also pointed out the necessity for better documentation and integration capabilities.

Ease of Deployment and Customer Service: Amazon Redshift is easy to deploy on the public cloud but offers limited flexibility for hybrid environments. Its customer service, although well-regarded, typically requires a paid plan for adequate technical support. Dremio provides versatile deployment options, accommodating public, hybrid, and on-premises settings, with reliable customer service that follows a similar paid plan model as Amazon Redshift.

Pricing and ROI: Amazon Redshift is cost-effective for large-scale data needs, with potential cost increases due to complex configurations. The pay-as-you-use model is practical, showing a good ROI when transitioning from on-premises systems. While Dremio's initial cost might be higher, it reflects its data integration value, offering substantial ROI in data governance-focused environments.

To learn more, read our detailed Amazon Redshift vs. Dremio Report (Updated: September 2026).

Amazon Redshift vs. Dremio

September 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

ROI

Sentiment score

6.0

Some entities quickly achieved cost savings and ROI, while others face challenges with optimization and evaluating benefits.

Sentiment score

4.0

Dremio offers cost savings and efficiency by reducing infrastructure needs and simplifying data source integration on data lakes.

We earned back our investment in Amazon Redshift within the first year.

For more quotes and insights, download the Amazon Redshift report

Data Engineer at a tech vendor with 10,001+ employees

Dremio surely saves time, reduces costs, and all those things because we don't have to worry so much about the infrastructure to make the different tools communicate.

For more quotes and insights, download the Dremio report

SR BI developer at BRQ Digital Solutions

Customer Service

Sentiment score

6.8

Amazon Redshift support is efficient yet costly, praised for documentation, but phone contact and complex issue resolution face delays.

Sentiment score

6.1

Dremio's customer service is highly praised for responsiveness, with Gold plan users enjoying positive interactions despite some limitations.

Whenever we need support, if there is an issue accessing stored data due to regional data center problems, the Amazon team is very helpful and provides optimal solutions quickly.

Pavan Kum

Analyst at Cepstrum(EEE Students Society), IIT Guwahati

Documentation that allows anyone with prior knowledge of Redshift or SQL to resolve technical issues.

For more quotes and insights, download the Amazon Redshift report

Data Engineer at a tech vendor with 10,001+ employees

It's costly when you enable support.

Ritesh Purbey

Senior Analyst at ESRI INDIA

I would rate customer support a ten out of ten.

Director

We contact the technical support at least weekly; currently, it's more or less daily because we face performance issues, crashes of queries sometimes, and we also need support for configuration of the query engines and so on.

Baptiste Bergelin

Data Architect at a consultancy with 51-200 employees

We have had to reach out for customer support many times, and they respond, so they are pretty supportive about some long-term issues.

For more quotes and insights, download the Dremio report

SR BI developer at BRQ Digital Solutions

Scalability Issues

Sentiment score

7.3

Amazon Redshift is highly scalable with flexible cluster adjustments, despite some challenges at larger scales and heavy loads.

Sentiment score

7.3

Dremio's scalability excels, with user-configurable auto-scaling on Kubernetes/Docker, meeting large-scale needs, but some features require licensing.

The scalability part needs improvement as the sizing requires trial and error.

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

We have successfully increased our storage space, which was a smooth process without server crashes before or after scaling.

For more quotes and insights, download the Amazon Redshift report

Data Engineer at a tech vendor with 10,001+ employees

Dremio's scalability can handle growing data and user demands easily.

SR BI developer at BRQ Digital Solutions

Internally, if it's on Docker or Kubernetes, scalability will be built into the system.

KamleshPant

Senior Software Architect at USEReady

Dremio's scalability depends on your hardware and your deployment.

For more quotes and insights, download the Dremio report

Director

Stability Issues

Sentiment score

7.3

Opinions on Amazon Redshift's stability vary, with some praising reliability and others noting issues in large clusters or maintenance.

Sentiment score

7.2

Dremio users report stable performance overall, despite occasional memory leaks, scalability issues, and the need for frequent monitoring.

Amazon Redshift is a stable product, and I would rate it nine or ten out of ten for stability.

For more quotes and insights, download the Amazon Redshift report

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

I rate Dremio a nine in terms of stability.

For more quotes and insights, download the Dremio report

SR BI developer at BRQ Digital Solutions

We refactored the query, and that worked, but it still doesn't make you confident to go to production with a product that might crash depending on the query you send it.

Baptiste Bergelin

Data Architect at a consultancy with 51-200 employees

Room For Improvement

Amazon Redshift users face challenges with performance, integration, cost, and features, preferring improved solutions like Snowflake's offerings.

Dremio users face issues with performance, connectors, learning curve, and desire better integration and schema flexibility.

They should bring the entire ETL data management process into Amazon Redshift.

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

Integration with AI could be a good improvement.

Pavan Kum

Analyst at Cepstrum(EEE Students Society), IIT Guwahati

Integration with AI features could elevate its capabilities and popularity.

For more quotes and insights, download the Amazon Redshift report

Data Engineer at a tech vendor with 10,001+ employees

Starburst comes with around 50 connectors now.

KamleshPant

Senior Software Architect at USEReady

Before we wrap up, I want to add that Dremio is lacking a semantic layer in a manner that the user can just choose dimensions, metrics, and filters to query the data.

For more quotes and insights, download the Dremio report

Director

It should be easier to get Arctic or an open-source version of Arctic onto the software version so that development teams can experiment with it.

reviewer2769915

Data Consultant at a comms service provider with 201-500 employees

Setup Cost

Amazon Redshift offers mid-to-high pricing, seen as reasonable due to its scalability and potential cost-effectiveness compared to competitors.

Dremio offers cost-effectiveness but licensing is costly, leading some users to prefer the community version for scalability.

The cost of technical support is high.

Ritesh Purbey

Senior Analyst at ESRI INDIA

It's a pretty good price and reasonable for the product quality.

For more quotes and insights, download the Amazon Redshift report

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

The pricing of Amazon Redshift is expensive.

reviewer1099677

Co-Founder, Director at a tech consulting company with 51-200 employees

I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.

Burak Uğur

Data Engineer at a tech services company with 201-500 employees

I had a good experience with pricing, as the pricing seems okay to me and the client.

For more quotes and insights, download the Dremio report

Director

Dremio does have a core of the engine that is open-source, but all the important features for the enterprise version are under license.

Baptiste Bergelin

Data Architect at a consultancy with 51-200 employees

Valuable Features

Amazon Redshift offers scalability, fast queries, AWS integration, flexibility, security, cost-effectiveness, easy setup, and compatibility for complex data management.

Dremio excels in data virtualization, federated queries, and integration, enhancing data management and access with efficient tools.

Amazon Redshift's performance optimization and scalability are quite helpful, providing functionalities such as scaling up and down.

For more quotes and insights, download the Amazon Redshift report

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

Scalability is also a strong point; I can scale it however I want without any limitations.

reviewer1099677

Co-Founder, Director at a tech consulting company with 51-200 employees

The specific features of Amazon Redshift that are beneficial for handling large data sets include fast retrieval due to cloud services and scalability, which allows us to retrieve data quickly.

Pavan Kum

Analyst at Cepstrum(EEE Students Society), IIT Guwahati

Having everything under one system and an easier-to-work-with interface, along with having API integrations, adds significant value to working with Dremio.

reviewer2769915

Data Consultant at a comms service provider with 201-500 employees

Dremio has positively impacted my organization as nowadays we are connected to multiple databases from multiple environments, multiple APIs, and applications, and Dremio organizes everything in an amazing way for me.

Joao Silveira

Data Analyst at a insurance company with 501-1,000 employees

Multiple data sources can be queried in one query, and it is not just a query engine.

Burak Uğur

Data Engineer at a tech services company with 201-500 employees

For more quotes and insights, download the Dremio report

Categories and Ranking

Amazon Redshift

Ranking in Cloud Data Warehouse

7th

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Warehouse (6th), Database Management Systems (DBMS) (9th)

Dremio

Ranking in Cloud Data Warehouse

10th

Average Rating

8.4

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Science Platforms (9th)

Mindshare comparison

As of November 2026, in the Cloud Data Warehouse category, the mindshare of Amazon Redshift is 7.0%, down from 7.6% compared to the previous year. The mindshare of Dremio is 4.3%, down from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Amazon Redshift	7.0%
Dremio	4.3%
Other	88.7%

Cloud Data Warehouse

Featured Reviews

Optimized restaurant analytics has driven faster insights and streamlined daily reporting

Data Engineer at a tech vendor with 10,001+ employees

Amazon Redshift offers massive parallel processing capability, allowing it to handle millions of records, along with integration with other AWS features such as S3 and QuickSight. The column-level storage supports high performance and easy data retrieval compared to other tools. The integration with S3 has helped my team immensely since S3 is our starting source, and the direct integration with Amazon Redshift simplifies the transformation and loading process. Columnar storage has benefited our performance significantly, allowing us to extract specific rows from tables with years of data much faster than other tools with row-level storage. Amazon Redshift has positively impacted our organization by significantly improving query performance and speed. Features such as easy integration with S3 allow us to process millions of records efficiently, ultimately saving us nearly one hour per day for our project.

Read full review

Has simplified complex data integration workflows and supported consistent reporting across multiple sources

SR BI developer at BRQ Digital Solutions

We also have a close relationship with the team that does the Dremio maintenance for the database, like upgrading the versions and they know about some specific problems we had in the past, such as a memory leak. We had a memory leak on some versions, which sometimes stopped the service. Since we are using Dremio installed like a server, not a SaaS solution, many times we need to stop and restart the service to clear all the cache and all that, and this is the thing I should add. I see that many times the new versions of Dremio have not fixed old bugs, and in some new versions, old problems that were previously fixed come back again, so I think the upgrade part could use improvement. I remember using some features in the past, like pivot tables, which proved to be really difficult, but I know this is a fault also for other vendors. Pivoting, transposing, and unpivoting are often not so good. CTEs also many times prove to be not so good, so I think these two main items could be improved significantly if they standardize them.

Read full review

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Construction Company

11%

Outsourcing Company

10%

Manufacturing Company

10%

Financial Services Firm

22%

Outsourcing Company

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	20
Large Enterprise	30

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	6
Large Enterprise	5

Questions from the Community

How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?

Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different dat...

What is your experience regarding pricing and costs for Amazon Redshift?

My experience with pricing and setup cost is satisfactory, as we have been loyal clients of Amazon since the beginning of our organization. However, I am not aware of the exact costs associated wit...

What needs improvement with Amazon Redshift?

Amazon Redshift could improve by enhancing its UI to be more user-friendly for non-technical users and by offering better cost management, as similar tools tend to be less expensive. Additionally, ...

What is your experience regarding pricing and costs for Dremio?

I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.

What needs improvement with Dremio?

I think Dremio can be improved to query faster than multiple sources and big data lakehouses. The community version could be updated for new data catalog connections. I think the documentation is s...

What is your primary use case for Dremio?

I have been using Dremio to select multiple data sources, retrieve multiple data sources, and create and maintain Iceberg tables for the data lakehouse. My main use case for Dremio is to actively c...

Snowflake vs Amazon Redshift

Comparisons

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Teradata vs Amazon Redshift

Compared 7% of the time

Microsoft Azure Synapse Analytics vs Amazon Redshift

Compared 6% of the time

IBM Db2 Warehouse on Cloud vs Amazon Redshift

Compared 5% of the time

Amazon EMR vs Amazon Redshift

Compared 5% of the time

More Amazon Redshift Competitors

Databricks vs Dremio

Compared 14% of the time

Snowflake vs Dremio

Compared 12% of the time

BigQuery vs Dremio

Compared 4% of the time

Starburst Enterprise vs Dremio

Compared 3% of the time

Altair RapidMiner vs Dremio

Compared 2% of the time

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Product Reports

Download Amazon Redshift product report

Amazon Redshift

October 2026

Download Dremio product report

October 2026

Also Known As

No data available

Dremio AWS - BYOL

Overview

Amazon Redshift is a dynamic data warehousing and analytics platform offering scalability and seamless AWS integration for high-performance query processing and diverse data management.

Amazon Redshift provides robust data integration capabilities with AWS services like S3 and QuickSight, enabling efficient data warehousing and analytics. It is known for fast query performance due to its columnar storage and can handle diverse file formats. With a user-friendly SQL interface, Redshift supports data compression and offers a strong cost-performance ratio. Its secure VPC configurations and compatibility with data science tools enhance its functionality, although there is room for improving snapshot restoration, dynamic scaling, and processing large datasets.

What are the key features of Amazon Redshift?

Scalability: Allows growth with business needs, accommodating increasing data volumes.
Massive Parallel Processing: Speeds up query performance through parallel data processing.
Seamless AWS Integration: Connects smoothly with services like S3 and QuickSight for enhanced functionality.
Columnar Storage: Enhances query performance by storing data in columns.
User-friendly SQL Interface: Simplifies data query and manipulation.
Data Compression: Efficiently compresses data to reduce storage costs.

What benefits should users look for in reviews?

Cost-Performance Ratio: Offers competitive pricing with high processing efficiency.
Fast Query Performance: Delivers quick data retrieval and processing speeds.
Security Features: Ensures data security through VPC configurations.
Integration Flexibility: Easily integrates with data science tools and BI platforms.

In industries, Amazon Redshift is essential for managing extensive datasets for business intelligence, operational insights, and reporting. It supports data integration from ERPs and S3, handles SQL queries for comprehensive analysis, and facilitates data storage and transformation. Companies use it for predictive modeling and connect with BI tools like Tableau and Power BI to derive actionable insights.

Amazon Web Services (AWS)

Dremio offers a comprehensive platform for data warehousing and data engineering, integrating seamlessly with data storage systems like Amazon S3 and Azure. Its main features include scalability, query federation, and data reflection.

Dremio's core strength lies in its ability to function as a robust data lake query engine and data warehousing solution. It facilitates the creation of complex queries with ease, thanks to its support for Apache Airflow and query federation across endpoints. Despite challenges with Delta connector support, complex query execution, and expensive licensing, users find it valuable for managing ad-hoc queries and financial data analytics. The platform aids in SQL table management and BI traffic visualization while reducing storage costs and resolving storage conflicts typical in traditional data warehouses.

What are Dremio's most valuable features?

Native Error Interfaces: Simplifies error detection and troubleshooting
Integration with Apache Airflow: Enhances workflow automation capabilities
Scalability: Effortlessly handles growing data demands
Role-Based Access Management: Provides secure data access control
Data Reflection: Optimizes query performance automatically
Query Federation: Supports queries across multiple endpoints seamlessly
Data Cataloging and Virtualization: Offers streamlined data organization

What benefits and ROI should users look for?

Reduced Data Storage Costs: Efficiently manages data to minimize storage expenses
Improved Query Performance: Enhances processing speed for large datasets
Flexibility in Integration: Easily connects with storage solutions like Oracle and MySQL
Enhanced Data Management: Supports comprehensive data analysis workflows

Dremio is primarily implemented in industries requiring extensive data engineering and analytics, including finance and technology. Companies use it for constructing data frameworks, efficiently processing financial analytics, and visualizing BI traffic. It acts as a viable alternative to AWS Glue and Apache Hive, integrating seamlessly with multiple databases, including Oracle and MySQL, offering robust solutions for data-driven strategies. Despite some challenges, its ability to reduce data storage costs and manage complex queries makes it a favorable choice among enterprise users.

Sample Customers

Liberty Mutual Insurance, 4Cite Marketing, BrandVerity, DNA Plc, Sirocco Systems, Gainsight, Blue 449

UBS, TransUnion, Quantium, Daimler, OVH