Amazon Aurora vs Exasol Data Warehouse comparison

Amazon Web Services (AWS) and Exasol are both solutions in the Relational Databases Tools category. Amazon Web Services (AWS) is ranked #5 with an average rating of 8.6, while Exasol is ranked #34. Amazon Web Services (AWS) holds a 3.2% mindshare in SQL, compared to Exasol’s 1.4% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Exasol users who would recommend it.

Amazon Aurora

Read 21 Amazon Aurora reviews

3,447 Views
3,206 Comparison Views

100% willing to recommend

Exasol Data Warehouse

Read 8 Exasol Data Warehouse reviews

1,658 Views
1,476 Comparison Views

100% willing to recommend

Amazon Aurora

Exasol Data Warehouse

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 4, 2025

Exasol Data Warehouse and Amazon Aurora compete in data management. Amazon Aurora has an edge due to advanced features, despite higher costs. Exasol's pricing and efficient support are notable, attracting cost-conscious customers.

Features: Exasol offers high-performance analytics, scalability, and seamless Tableau integration, eliminating indexing concerns with automatic query optimization. Aurora provides compatibility with MySQL and PostgreSQL, secure multi-region replication, and advanced auto-scaling combined with AWS ecosystem benefits.

Room for Improvement: Exasol could enhance its ease of use by incorporating more automation in maintenance tasks. It may also expand its integration capabilities beyond current BI tools and provide more granular role management. Aurora, while robust, could improve in simplifying setup complexity, reducing cost barriers for smaller businesses, and offering more flexible maintenance options.

Ease of Deployment and Customer Service: Exasol simplifies deployments with quick setup and responsive service, minimizing configuration hassle. Aurora benefits from AWS integration for seamless scaling but may involve more intricate setup. While Aurora's support relies on AWS's overarching service structure, Exasol's dedicated approach offers a more personalized touch.

Pricing and ROI: Exasol's pricing structure suits analytics-focused firms seeking competitive initial investments and solid ROI. Aurora's premium pricing aligns with its feature-rich offering, considered worthwhile for organizations prioritizing advanced scalability. Exasol appeals to cost-conscious buyers, while Aurora attracts those valuing expansive feature sets for long-term growth.

To learn more, read our detailed Amazon Aurora vs. Exasol Data Warehouse Report (Updated: August 2026).

Buyer's Guide

Amazon Aurora vs. Exasol Data Warehouse

August 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:

Categories and Ranking

Amazon Aurora

Ranking in Relational Databases Tools

5th

Average Rating

8.4

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Database Management Systems (DBMS) (6th)

Exasol Data Warehouse

Ranking in Relational Databases Tools

34th

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Relational Databases Tools category, the mindshare of Amazon Aurora is 3.2%, up from 2.8% compared to the previous year. The mindshare of Exasol Data Warehouse is 1.4%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Relational Databases Tools Mindshare Distribution
Product	Mindshare (%)
Amazon Aurora	3.2%
Exasol Data Warehouse	1.4%
Other	95.4%

Relational Databases Tools

Featured Reviews

SivashankarRajaram

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

Cloud database has delivered high performance and cost savings for data recovery and growth

Amazon can make better access levels and reduce costs for Amazon Aurora. A cost reduction would support multiple teams to adopt this solution since the cost is currently higher. Comparatively, we have the feature of scaling and everything we need. If you launch PostgreSQL on-premises, you need to have a separate DBA for maintenance and everything. If Amazon reduces the cost of Amazon Aurora, it would support large team adoption. A great feature to see in the next version of Amazon Aurora would be improvements in vectorization. In our PostgreSQL, we have pg_vector that helps with vectorizing many of the tables and that is used for data science projects. If Amazon improves this vectorization, it would be much more useful for data science and AI projects.

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Shubham-Agarwal

Manager - Projects at Cognizant

Fast query processing and easy-to-store all the data

There are very few companies that are using Exasol, but the majority of companies are using SQL Server, Cloud or IBM Db2 Database, or any other databases. Therefore, the resources are limited, which is my only concern. So if I face any issues, limited resources are available to help me resolve the issue with Exasol. From that perspective, it can be a bit of a struggle for me to find a solution. In the next release, I would like to see better compatibility issues. Currently, Exasol has limited compatibility with other software like Python and R. For example, If I talk about SQL Server, we can connect it to big data or Python, which is also compatible with different servers.

Read full review

Quotes from Members

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

Pros

"Amazon Aurora's best features are about scaling up and scaling down, which is perfect."

"Amazon Aurora is built on community databases and AWS has added additional features to it, allowing customers to have enterprise-level features at a lower cost."

"The solution’s scalability is good since we don’t need to take a maintenance window during unpredictable workloads. I like the solution’s behind-the-scenes happenings. It is a great feature."

"Amazon Aurora stands out for its ease of use in a managed environment, inbuilt security, continuous backups, numerous read replicas, multi-region automated replication, and seamless integration with other AWS services."

"The provision of custom read and write endpoints eliminates the need for managing a separate proxy load balancer."

"The most valuable features of Amazon Aurora include the global instance with the global writer endpoint, which allows failovers and instance switches without requiring changes in my code, thanks to the default global Route 53 endpoint."

"My overall experience with Amazon Aurora is very positive. I rate it ten out of ten for its reliability and efficiency."

"One of the most valuable features is storage scaling."

More Amazon Aurora pros

"This solution is extremely fast and very stable; you set it up and put your data on it and as long as it's structured, it self-tunes queries and doesn't require a database administrator."

"The solution is hands-off; you set it up insert your data and it self tunes queries."

"We can quickly scale the solution as it works on an MPP system."

"Performance is a top priority, and it excels in this aspect."

"We mainly chose Exasol for its performance reasons."

"The speed is very good compared to other databases, like SQL Server or Oracle."

"It is easy to scale."

"The most valuable feature of Exasol is its speed."

More Exasol Data Warehouse pros

Cons

"Amazon Aurora should upgrade its base PostgreSQL versions more frequently and offer all PostgreSQL extensions."

"I would like to see some tutorials from Amazon for Aurora because I'm too new to it."

"The product's distributed query process for MySQL needs improvement."

"I don't use Amazon Aurora's global database feature; I just use the local feature."

"In my experience, I didn't see the claimed speed, and when you factor in the cost, or the extra cost of Aurora compared to a normal database, it didn't justify the cost from a performance standpoint, but it did justify the cost because we didn't have to have multiple instances, Redis caches, and other things like that."

"In Oracle, tools like Veridata allow for comparing databases and certifying data accuracy, even offering repair capabilities, which are missing in Aurora. There should be a similar comparison tool in Aurora."

"I would like to see more AI-related features in future releases."

"There are tuning challenges. The same methods used for tuning in RDS might not work in Aurora, and some functionalities available in MySQL may not be compatible with Aurora."

More Amazon Aurora cons

"It would be beneficial if the updates would occur more often."

"It's not cloud-native so many maintenance operations require downtime."

"They don't talk very well to with other products when it comes to connectivity. Integration is lacking."

"Lacks a cloud-based platform."

"There are limited resources available to help me resolve the issue with Exasol."

"The only area where we found it could improve was in custom role creation and security, and it was difficult to work with."

"You have to install Exasol drivers, and it's not easy to find or implement a driver into different systems."

"They should improve the security features for MPP processing."

More Exasol Data Warehouse cons

Pricing and Cost Advice

"The tool’s pricing depends on the instance type. For cost optimization purposes, we use the result instance category."

"There is no need to buy a license for the product. We can pay as per the use case."

"It is quite expensive."

"I would rate the pricing a six out of ten, with ten being expensive."

"The price could be lower compared to its competitors."

"It is an expensive solution."

"The solution's cost is mid-ranged."

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Healthcare Company

11%

University

11%

Manufacturing Company

Outsourcing Company

13%

Construction Company

11%

Manufacturing Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	4
Large Enterprise	14

By reviewers
Company Size	Count
Small Business	1
Midsize Enterprise	1
Large Enterprise	6

Questions from the Community

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

The pricing for Amazon Aurora is different from DocumentDB because DocumentDB is cheaper. However, when you manage the administration more closely, you can control costs better with Amazon Aurora. ...

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What needs improvement with Amazon Aurora?

See all answers

What is your primary use case for Amazon Aurora?

Amazon Aurora is a service provided by AWS, and we received support from AWS for our implementation. The direction we are moving toward is specifically Amazon Aurora PostgreSQL.

See all answers

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Comparisons

YugabyteDB vs Amazon Aurora

Compared 12% of the time

Oracle Database vs Amazon Aurora

Compared 12% of the time

SQL Server vs Amazon Aurora

Compared 9% of the time

Oracle Database Cloud Service vs Amazon Aurora

Compared 8% of the time

CockroachDB vs Amazon Aurora

Compared 7% of the time

More Amazon Aurora Competitors

SQL Server vs Exasol Data Warehouse

Compared 11% of the time

Teradata vs Exasol Data Warehouse

Compared 9% of the time

Oracle Database vs Exasol Data Warehouse

Compared 8% of the time

IBM Db2 Database vs Exasol Data Warehouse

Compared 7% of the time

Oracle Database In-Memory vs Exasol Data Warehouse

Compared 6% of the time

More Exasol Data Warehouse Competitors

Product Reports

Buyer's Guide

Amazon Aurora

August 2026

Download Amazon Aurora product report

Buyer's Guide

Exasol Data Warehouse

August 2026

Download Exasol Data Warehouse product report

Overview

Amazon Aurora offers a relational database service with high availability and compatibility with MySQL and PostgreSQL. It is designed for efficient scalability and seamless integration within AWS, making it optimal for applications requiring robust performance and reliability.

Amazon Aurora distinguishes itself through its managed maintenance, ensuring high operational efficiency. It provides users with the ability to auto-scale their database resources, allowing businesses to maintain cost efficiency without sacrificing performance. The service includes robust disaster recovery options and supports up to sixteen read replicas, which are critical for mission-critical applications. Users benefit from smooth, cross-region replication and integration capabilities with other AWS services, enhancing data reliability and accessibility.

What are the most important features of Amazon Aurora?

Multiple-read and single-write capabilities: Offers versatile data handling for improved performance.
Seamless SQL standardization: Ensures compatibility with existing systems.
Auto-scaling: Adjusts resources dynamically based on workload demands.
High performance: Provides efficient data processing and fast response times.
Integration with AWS services: Enhances functionality through a secure ecosystem.

What benefits and ROI should users consider?

Cost management: Efficient scaling reduces unnecessary expenditure.
Reliability: Fault tolerance and replication ensure data availability.
Operational efficiency: Managed maintenance lowers administrative overhead.
Scalability: Supports seamless service adaptation to changing business needs.

Amazon Aurora is extensively used across various industries such as finance, e-commerce, and healthcare, supporting internal applications with its relational database prowess. Many organizations leverage its serverless capabilities and cost-effective scalability for developing business intelligence and payment processing solutions. The seamless migration assistance from Oracle databases further underscores its appeal for enterprises looking to optimize database performance and reduce operational costs.

Amazon Web Services (AWS)

Exasol Data Warehouse is renowned for its exceptional speed and automatic optimization, making it user-friendly. It enhances data processing on platforms such as Tableau, ensuring efficient dashboards for users across countries.

Exasol Data Warehouse offers an impressive performance by outperforming competitors like SQL Server and Oracle. Its automatic optimization and hands-off setup simplify deployment, while robust SQL support and self-tuning capabilities improve workflows. Users benefit from its high processing speed, supporting efficient data queries and broader workflows, alongside an intuitive interface and comprehensive documentation. Despite its performance strengths, it struggles with global recognition, connectivity, and integration. Challenges include custom role creation and security, with limited row-level security support. Users seek more frequent updates and better compatibility with languages such as Python and R. It requires specific drivers, is not cloud-native, and has a high cost. With limited resources available, security features for MPP processing need enhancement.

What are the key features of Exasol?

Impressive Speed: Outperforms counterparts in data processing, enhancing efficiency.
Automatic Optimization: Boosts performance and ease of use.
Robust SQL Support: Facilitates seamless data handling and queries.
Self-Tuning Capabilities: Reduces manual intervention for users.
Intuitive Interface: Enhances user engagement and accessibility.

What benefits should users look for in Exasol?

Enhanced Performance: Streamlines and accelerates BI functions.
Improved Dashboard Efficiency: Increases effectiveness on platforms like Tableau.
Ease of Use: Simplifies set-up with hands-off setup and self-tuning.
Broad Integration: Acts as backend for tools like MicroStrategy.
Central Data Repository: Supports critical data management across regions.

Exasol Data Warehouse is implemented to enhance performance in reporting systems and development processes, serving teams in Mexico, Colombia, and Brazil. It acts as a backend for reporting tools such as MicroStrategy while accelerating BI functions. It supports the resolutions of data issues from tools like Tableau, provides ad-hoc analysis, and manages critical data points efficiently.

Exasol

Sample Customers

Dow Jones, Arizona State University, Verizon, Capital One, United Nations, Nielsen, Autodesk, Fanduel

1&1 Internet SE 11880 Internet Services AG AB Svenska Spel Accarda AG Aera Technology Inc. AGRAVIS Raiffeisen AG Apotheken-Rechen-Zentrum GmbH AQR Capital Management, LLC arvato distribution GmbH ARZ Allgemeines Rechenzentrum GmbH Badoo Limited Baur Versand (GmbH & Co. KG) BIScience Ltd Blocket Blue Yonder GmbH Codilink UK Ltd T/A Coniq crealytics GmbH dailyme TV GmbH Dailymotion S.A. Dataforce Verlagsgesellschaft für Business Information mbH Deutsche Postbank AG Digitales Rezept Zentrum GmbH DIKW Groep direct services Gütersloh GmbH DR Technologies Ltd. dress-for-less GmbH econda GmbH emetriq GmbH empiriecom GmbH & Co. KG Flaconi GmbH Fresenius Netcare GmbH Fyber GmbH GfK SE Grant Street Group, Inc. Gruner + Jahr GmbH Gymshark UK Hahn Air Lines GmbH Hermes Einrichtungs Service GmbH & Co. KG INNOVATIVE SCHEDULING, LLC internetstores GmbH INTERSPORT Deutschland eG IQVIA Commercial GmbH & Co. OHG IQVIA Commercial Sp. z o.o. IQVIA Incorporated iVantage Health Analytics K - Mail Order GmbH & Co. KG LIQ CORP SA Manor AG Basel Match2Lists Limited MEDION AG Midasplayer AB Monsoon Accessorize Limited m-pathy GmbH msales Ltd. MTG Modern Services AB MW Aviation GmbH & Co. KG Myntra Designs Pvt Ltd Netzeffekt GmbH New Company Services Ltd. NOVENTI HealthCare GmbH Olympus Europa SE & Co. KG Operation Fistula OpsDataStore OTTO (GmbH & Co KG) Panda Retail Co. PAPSTAR GmbH Piedmont Healthcare, Inc. Questback GmbH RatePAY GmbH Revolut Ltd. Saarland-Sporttoto GmbH Sagarmatha Ltd. SIA Damara Technologies Supermärkte Nord Vertriebs GmbH & Co. KG The National Research Center for College & University Admissions, Inc. United Utilities Water Ltd. Verlag C.H. Beck oHG Vocal Planet Ltd. Vodafone Group Services GmbH Webtrekk GmbH wer liefert was? GmbH Windeln.de SE Wooga GmbH XING SE Zalando SE

Buyer's Guide

Amazon Aurora vs. Exasol Data Warehouse

August 2026

Free Report: Amazon Aurora vs. Exasol Data Warehouse

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