Microsoft Parallel Data Warehouse vs Oracle Big Data Appliance comparison

Microsoft and Oracle are both solutions in the Data Warehouse category. Microsoft is ranked #11 with an average rating of 8.3, while Oracle is ranked #15 with an average rating of 8.0. Microsoft holds a 3.2% mindshare in Data Warehouse, compared to Oracle’s 2.5% mindshare. Additionally, 87% of Microsoft users are willing to recommend the solution, compared to 75% of Oracle users who would recommend it.

Microsoft Parallel Data War...

Read 40 Microsoft Parallel Data Warehouse reviews

1,947 Views
1,519 Comparison Views

87% willing to recommend

Oracle Big Data Appliance

Read 6 Oracle Big Data Appliance reviews

1,184 Views
888 Comparison Views

75% willing to recommend

Microsoft Parallel Data War...

Oracle Big Data Appliance

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Executive SummaryUpdated on Dec 18, 2024

Microsoft Parallel Data Warehouse and Oracle Big Data Appliance are both data analytics and warehousing solutions. Oracle Big Data Appliance offers a broader set of features, potentially making it a more comprehensive choice for businesses despite its higher cost.

Features: Microsoft Parallel Data Warehouse integrates seamlessly with existing Microsoft systems, supports extensive data manipulation, and provides robust data integrity features. Oracle Big Data Appliance supports both Hortonworks and Cloudera Hadoop distributions, has Spark on YARN integration for faster processing, and offers enhanced language processing.

Room for Improvement: Microsoft Parallel Data Warehouse could benefit from expanding its support for non-Microsoft ecosystems, enhancing scalability options, and improving data processing speeds. Oracle Big Data Appliance could improve user accessibility for non-technical users, simplify its extensive feature set, and provide more resources for faster deployment.

Ease of Deployment and Customer Service: Microsoft Parallel Data Warehouse integrates easily with other Microsoft products, simplifying deployment and leveraging quick customer service. Oracle Big Data Appliance, albeit complex, compensates with high-quality support to assist through deployment and usage challenges.

Pricing and ROI: Microsoft Parallel Data Warehouse is known for cost-effectiveness, providing competitive ROI especially for businesses keen on budget efficiency. Oracle Big Data Appliance, though more expensive, is seen as a beneficial long-term investment due to its extensive features, which can translate into significant ROI.

To learn more, read our detailed Microsoft Parallel Data Warehouse vs. Oracle Big Data Appliance Report (Updated: April 2026).

Buyer's Guide

Microsoft Parallel Data Warehouse vs. Oracle Big Data Appliance

April 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

Microsoft Parallel Data War...

Ranking in Data Warehouse

11th

Average Rating

7.8

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Oracle Big Data Appliance

Ranking in Data Warehouse

15th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Data Warehouse category, the mindshare of Microsoft Parallel Data Warehouse is 3.2%, up from 0.9% compared to the previous year. The mindshare of Oracle Big Data Appliance is 2.5%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Microsoft Parallel Data Warehouse	3.2%
Oracle Big Data Appliance	2.5%
Other	94.3%

Data Warehouse

Featured Reviews

HassanFatemi

CEO at Smart Data-Driven Solutions

Has handled large volumes of data effectively but still needs cost flexibility

There could be improvements on the cost side of Microsoft Parallel Data Warehouse because it is still considered to be quite expensive by a lot of users, and many companies are not interested in solutions with parallel data warehousing due to this expense. Addressing the cost would be the number one area for improvement. Additionally, I have not worked recently with it, so I don't know if this feature already exists, but if it doesn't, having an elastic feature that adjusts the service's power dynamically based on the workload would be beneficial instead of fixing the power at a specific level.

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reviewer1031826

Analytics Lead at a tech vendor with 10,001+ employees

Platinum partnership leverages advanced storage and fosters seamless data integration

Areas of Oracle Big Data Appliance that can be improved include the pricing perspective because nowadays they have competition. We have so many technologies that have come to the market for less than even one-fourth or one-fifth of the Oracle price. For my side, the last time I worked with Oracle was in '21, '22. The price is a challenge that they have to look after. From the storage and data management perspective, I cannot recall anything that they have to improve, but they have to improve the visualization part significantly because they offer Oracle BI, which is an extremely not-matured application.

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Quotes from Members

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

Pros

"Collecting the data through SSIS packages from different sources and putting them all in one data repository is the most powerful thing."

"It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time."

"I am very satisfied with the customer service/technical support."

"This is a great product for big data analytics as it can challenge other MPPs quite well."

"It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time."

"It is very strong, scalable, and has tons of features."

"The most valuable feature for me is querying."

"Most features on the SQL Server are quite useful to us."

More Microsoft Parallel Data Warehouse pros

"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."

"Big Data responds to my needs."

"This is a comprehensive solution that is easy to deploy."

"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."

"The most valuable feature is that it can be used in conjunction with Spark memory processing, and our processing time has gone to 20 minutes from what used to be two or three hours on the mainframe."

"We could work on large unstructured datasets from different parts of the world on Facebook and Twitter to get better insights."

"The best feature of Oracle Big Data Appliance, from a price perspective for the storage, is because they have technology called the ZFS technology; it offers huge storage with a decent price."

More Oracle Big Data Appliance pros

Cons

"We'd like to see it be a bit more compatible with other solutions."

"We find the cost of the solution to be a little high."

"More tools to help designers should be included."

"When there are many users or many expensive queries, it can be very slow."

"Concurrent queries are limited to 32, making it more of a data storage mechanism instead of an active DWH solution."

"This tool needs a lot of memory for processing."

"I would like to see better visualization features."

"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."

More Microsoft Parallel Data Warehouse cons

"We need to display the results on our website. I think there is another product that joins with it to give you the possibility."

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

"The product should be simplified for the average user."

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

"We had to pursue several performance tuning measures to bring up the system to scale."

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."

Pricing and Cost Advice

"Microsoft has an agreement with the government in our country, so our customers get their licensing costs from the Ministry. Whenever we work with any government, company, or government institute, which is mainly what we are doing, that license comes directly from the Ministry of Technology and Information."

"The tool could be expensive if we need to manage a lot of data."

"The solution's pricing is fairly decent for organizations with huge data sizes."

"I think the program is well-priced compared to the other offerings that are out in the market."

"All the features that we use do not require any additional subscription or yearly fees."

"They offer an annual subscription. The pricing depends on the size of the environments."

"The solution is cost-effective."

"Technical support is an additional fee and is expensive."

"Oracle's prices are too high compared to others in the market."

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Top Industries

By visitors reading reviews

Construction Company

18%

Financial Services Firm

12%

Marketing Services Firm

Manufacturing Company

Financial Services Firm

25%

Manufacturing Company

14%

Government

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	16
Midsize Enterprise	6
Large Enterprise	22

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 Microsoft Parallel Data Warehouse?

Microsoft Parallel Data Warehouse is very expensive.

See all answers

What needs improvement with Microsoft Parallel Data Warehouse?

The pricing could be better; I think it actually just went up.

See all answers

What is your primary use case for Microsoft Parallel Data Warehouse?

The basic use case for us is virtual machines. In real estate, we use it for our operations. They handle large data sets well, and the performance is good during those times.

See all answers

What needs improvement with Oracle Big Data Appliance?

See all answers

What is your primary use case for Oracle Big Data Appliance?

The typical use case for Oracle Big Data Appliance, which my clients use, is usually that the customer who has an Oracle application uses it because they can leverage the storage part. I don't need...

See all answers

Comparisons

Oracle Exadata vs Microsoft Parallel Data Warehouse

Compared 11% of the time

Teradata vs Microsoft Parallel Data Warehouse

Compared 9% of the time

OpenText Analytics Database (Vertica) vs Microsoft Parallel Data Warehouse

Compared 7% of the time

biGENIUS vs Microsoft Parallel Data Warehouse

Compared 5% of the time

VMware Tanzu Data Solutions vs Microsoft Parallel Data Warehouse

Compared 4% of the time

More Microsoft Parallel Data Warehouse Competitors

IBM Integrated Analytics System vs Oracle Big Data Appliance

Compared 8% of the time

Apache Hadoop vs Oracle Big Data Appliance

Compared 7% of the time

Oracle Exadata vs Oracle Big Data Appliance

Compared 7% of the time

SAP BW4HANA vs Oracle Big Data Appliance

Compared 6% of the time

SAP IQ vs Oracle Big Data Appliance

Compared 5% of the time

More Oracle Big Data Appliance Competitors

Product Reports

Buyer's Guide

Microsoft Parallel Data Warehouse

April 2026

Microsoft Parallel Data Warehouse report

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Buyer's Guide

Data Warehouse

May 2026

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Also Known As

Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data Warehouse, MS Parallel Data Warehouse

No data available

Overview

Microsoft Parallel Data Warehouse offers high performance and usability with seamless SQL Server integration, handling large data efficiently with a user-friendly interface. Known for its cost-effectiveness and robust security, it excels in integrating data across Microsoft ecosystem.

Microsoft Parallel Data Warehouse efficiently manages large datasets from diverse sources, supporting a unified data approach. Its integration with SQL Server and compatibility with tools like Qlik enhances data management and decision-making capabilities. With impressive scalability and security features, it is widely used in sectors such as finance, healthcare, and logistics for analytics and reporting. However, users seek improvements in integration with non-Microsoft layers, memory usage, SQL configuration, and scalability.

What are the key features of Microsoft Parallel Data Warehouse?

Clustered Columnstore Index: Boosts performance for complex queries.
SQL Server Integration: Seamless connectivity with Microsoft's database solutions.
Data Volume Handling: Efficient management of large datasets.
Cost Management: Ability to pause operations for cost savings.
Security Measures: Ensures robust data protection.

What benefits do users expect when evaluating Microsoft Parallel Data Warehouse?

Performance Efficiency: High-speed data processing capabilities.
Cost-Effectiveness: Suitable pricing model in specific scenarios.
Scalability: Ability to grow with business needs.
Integration Capabilities: Compatibility with Microsoft products and SQL Server.

In industries like finance, healthcare, and logistics, Microsoft Parallel Data Warehouse supports analytics, reporting, and decision-making processes. Organizations utilize it to maintain historical data, develop business intelligence models, and create actionable dashboards, benefiting from its integration with key tools and efficient data management.

Microsoft

Oracle Big Data Appliance offers a comprehensive platform integrating ZFS technology and supporting Spark, designed to boost performance with Hadoop distributions, ensuring data security and accessibility across multiple languages.

Oracle Big Data Appliance presents an adaptable solution facilitating data consolidation with robust storage technology, crucial for central data repositories. Its Spark in-memory processing significantly reduces time through seamless integration with Hadoop distributions like Hortonworks and Cloudera. Role-based security enhances organizational data access, while multi-language support meets diverse processing requirements. Although challenges exist in AI capabilities and visualization tool efficiency, the platform remains valuable for entity-wide deployment.

What key features does Oracle Big Data Appliance offer?

Drag-and-Drop Interface: Enables non-technical users to build reports effortlessly.
ZFS Technology: Provides cost-effective storage solutions.
Spark on YARN Support: Enhances Hadoop performance with faster processing.
Security Roles: Ensures data access alignment with user privileges.
Multi-Language Support: Assists in handling diverse language processing needs.

What benefits should users look for when evaluating Oracle Big Data Appliance?

Centralized Data Management: Avoids the need for additional data warehouses.
Regulatory Reporting Facilitation: Eases compliance processes in sectors like Medicare.
Role-Based Reporting: Empowers end-users to create reports based on specific needs.
Consultation Integrations: Supports seamless data management when coupled with external services.

Oracle Big Data Appliance is predominantly used in healthcare and financial services, where data consolidation and regulatory compliance are crucial. Entities leverage Oracle's storage capabilities to maintain centralized repositories, expediting regulatory reporting and claim management processes, particularly benefiting sectors like Medicare. Consulting services frequently integrate Oracle platforms to enhance data management efficiency, especially for organizations utilizing Oracle applications.

Oracle

Sample Customers

Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel Europe

Caixa Bank

Buyer's Guide

Microsoft Parallel Data Warehouse vs. Oracle Big Data Appliance

April 2026

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