Microsoft Parallel Data Warehouse vs Snowflake Analytics comparison

Microsoft and Snowflake Computing are both solutions in the Cloud Data Warehouse category. Additionally, 87% of Microsoft users are willing to recommend the solution, compared to 100% of Snowflake Computing users who would recommend it.

Microsoft Parallel Data War...

Read 40 Microsoft Parallel Data Warehouse reviews

2,609 Views
2,087 Comparison Views

87% willing to recommend

Snowflake Analytics

Read 44 Snowflake Analytics reviews

3,188 Views
1,403 Comparison Views

100% willing to recommend

Microsoft Parallel Data War...

Snowflake Analytics

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Executive Summary

We performed a comparison between Microsoft Parallel Data Warehouse and Snowflake Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: August 2026).

Buyer's Guide

Cloud Data Warehouse

August 2026

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Helped 909,725 peers since 2012

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

4.9

Users find Microsoft Parallel Data Warehouse effective in managing data, integrating tools, with ROI potential despite indirect tracking.

Sentiment score

5.6

Users experience mixed ROI with Snowflake; it often improves operational efficiency, time savings, and cost control.

No quotes available

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

Snowflake Analytics has positively impacted our organization by saving about eight to ten hours per week, which we can use for advanced analytics and automation tasks.

Hemanthreddy Vakiti

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

For more quotes and insights, download the Snowflake Analytics report

Customer Service

Sentiment score

6.8

Microsoft Parallel Data Warehouse support is generally positive with responsive service, though some suggest enhancements in speed and Azure expertise.

Sentiment score

6.9

Snowflake Analytics support is often responsive and competent, but accessibility issues exist for non-major partners, despite strong community resources.

They are responsive and get back to us.

reviewer2254953

Service Desk Administrator at a real estate/law firm with 1,001-5,000 employees

I would rate my experience with technical support around six on a scale of 1 to 10 because I have not had a particular experience with technical support.

HassanFatemi

CEO at Smart Data-Driven Solutions

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

The Snowflake Analytics documentation is excellent.

reviewer2729628

Lead Analytics Consultant at a outsourcing company with 51-200 employees

Recently we had a two-day session where the Snowflake Analytics team provided a demo on Cortex AI and its features.

Garima Goel

Associate Principal Engineer at Nagarro

The technical support for Snowflake Analytics is excellent based on what I have heard from others.

Paresh_Nayak

Data Governance Architect at Sterlite Technologies Ltd

For more quotes and insights, download the Snowflake Analytics report

Scalability Issues

Sentiment score

7.3

Microsoft Parallel Data Warehouse is scalable with SQL benefits, but may lag behind Snowflake in large data handling.

Sentiment score

7.7

Snowflake Analytics offers exceptional scalability through auto-scaling, cloud integration, and efficient resource management, ideal for handling large data volumes.

We go from a couple of users to tons of users all the time, and it scales and handles things really well.

reviewer2254953

Service Desk Administrator at a real estate/law firm with 1,001-5,000 employees

I give the scalability an eight out of ten, indicating it scales well for our needs.

Ailton Souza

Architecture at a manufacturing company with 10,001+ employees

As a consultant, we hire additional programmers when we need to scale up certain major projects.

Ashok Bhadra

Associate Director at Sequentis

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

Storage is unlimited because they use S3 if it is AWS, so storage has no limit.

KamleshPant

Senior Software Architect at USEReady

It supports both horizontal and vertical scaling effectively.

Paresh_Nayak

Data Governance Architect at Sterlite Technologies Ltd

Maintaining security and data governance becomes easier with an entire data lake in place, and the scalability improves performance.

Garima Goel

Associate Principal Engineer at Nagarro

For more quotes and insights, download the Snowflake Analytics report

Stability Issues

Sentiment score

8.1

Microsoft Parallel Data Warehouse is stable, reliable, handles large volumes well, with occasional speed issues on vast datasets.

Sentiment score

8.4

Snowflake Analytics is highly stable, supported by major cloud providers, with strong performance and minimal technical issues reported.

Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.

Ailton Souza

Architecture at a manufacturing company with 10,001+ employees

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

Snowflake Analytics has been stable and reliable in my experience.

Garima Goel

Associate Principal Engineer at Nagarro

Snowflake Analytics is very stable; I have never experienced any crash downs or server issues.

Hemanthreddy Vakiti

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

Snowflake Analytics is stable, scoring around eight point five to nine out of ten.

Paresh_Nayak

Data Governance Architect at Sterlite Technologies Ltd

For more quotes and insights, download the Snowflake Analytics report

Room For Improvement

Microsoft Parallel Data Warehouse needs better tool integration, scalability, compatibility, frequent updates, competitive pricing, and enhanced error messaging.

Snowflake Analytics struggles with data migration, integration, performance, cost issues, and needs better UI, job scheduling, and AWS support.

It would be better to release patches less frequently, maybe once a month or once every two months.

Ashok Bhadra

Associate Director at Sequentis

Addressing the cost would be the number one area for improvement.

HassanFatemi

CEO at Smart Data-Driven Solutions

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

Tcheupi Jonathan

Computer engineer at a engineering company with 5,001-10,000 employees

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

AIML-based SQL prompt and query generation could be an area for enhancement.

KamleshPant

Senior Software Architect at USEReady

If it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better.

Paresh_Nayak

Data Governance Architect at Sterlite Technologies Ltd

I would prefer Snowflake Analytics to improve their support response times, as sometimes the responses we receive are not very prompt and ticket assignments may not be timely.

Garima Goel

Associate Principal Engineer at Nagarro

For more quotes and insights, download the Snowflake Analytics report

Setup Cost

Microsoft Parallel Data Warehouse offers competitive pricing, suitable for large enterprises, but can be costly for high-performance needs.

Snowflake Analytics uses a pay-as-you-go model, emphasizing strategic design to manage costs, often seen as competitively priced.

Microsoft Parallel Data Warehouse is very expensive.

Ailton Souza

Architecture at a manufacturing company with 10,001+ employees

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.

AyindeHammed

BI Developer at DivVerse LLC

Snowflake is better and cheaper than Redshift and other cloud warehousing systems.

KamleshPant

Senior Software Architect at USEReady

Snowflake Analytics is quite economical.

Paresh_Nayak

Data Governance Architect at Sterlite Technologies Ltd

For more quotes and insights, download the Snowflake Analytics report

Valuable Features

Microsoft Parallel Data Warehouse boosts data loads, integrates with Power BI, and offers scalable BI with minimal costs.

Snowflake Analytics provides scalable, secure, and user-friendly analytics with cloud integration, supporting diverse data needs and flexible data sharing.

The columnstore index enhances data query performance by using less space and achieving faster performance than general indexing.

Vanessa Jin

BI/Data Warehouse Analyst at a healthcare company with 501-1,000 employees

Microsoft Parallel Data Warehouse is used in the logistics area for optimizing SQL queries related to the loading and unloading of trucks.

Ailton Souza

Architecture at a manufacturing company with 10,001+ employees

There's a feature that allows users to set alerts on triggers within reports, enabling timely actions on pending applications and effectively reducing waiting time.

Ashok Bhadra

Associate Director at Sequentis

For more quotes and insights, download the Microsoft Parallel Data Warehouse report

Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.

AyindeHammed

BI Developer at DivVerse LLC

Snowflake Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.

Paresh_Nayak

Data Governance Architect at Sterlite Technologies Ltd

Previously, we faced issues with slow queries due to traditional systems, but within Snowflake, we can assign separate virtual warehouses for reporting as well as data processing, ensuring that it does not impact tool performance and does not delay reporting to business users.

Hemanthreddy Vakiti

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

For more quotes and insights, download the Snowflake Analytics report

Categories and Ranking

Microsoft Parallel Data War...

Average Rating

7.8

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Warehouse (9th)

Snowflake Analytics

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Web Analytics (2nd), Cloud Data Warehouse (12th)

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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Garima Goel

Associate Principal Engineer at Nagarro

Have created secure cloud-based data lakes and improved real-time data processing using integrated AI features

There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems. We also have features such as pre-cached results, Time Travel, and fail-safe, which are very useful for restoring data if deleted accidentally, and the streams and data pipes that facilitate real-time ingestion are great features as well. Snowflake Analytics offers multiple new connectors, allowing me to connect it with Kafka, and with Snowpark, I can work with any programming language such as Python, Java, or Scala for data processing and analysis. The data sharing feature offered by Snowflake Analytics is good because it allows sharing specific sets of data to end customers or users from different Snowflake Analytics accounts without exposing the entire dataset for data security reasons. Snowflake Analytics' support for machine learning models and real-time insights has enhanced significantly. Originally, it wasn't strong in AI/ML, but now it has multiple models and forecasting capabilities, providing good competition to tools such as Databricks and Spark. In BI, I have worked majorly with Microsoft Power BI, and the integration with Snowflake Analytics is very easy. The way we integrate Snowflake Analytics with other on-premise systems just requires the warehouse details, username, passwords, and the account name, along with multiple options such as client ID and credentials for logging in and creating a session. The end-to-end encryption provided by Snowflake Analytics is very important because, in my previous firm, working in finance and investment management, data encryption is necessary due to the sensitive nature of customer data and the involvement of people's money. It's crucial to have encryption in transit and at rest, along with data masking features which Snowflake Analytics offers.

Read full review

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909,725 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Construction Company

24%

Financial Services Firm

14%

Outsourcing Company

Manufacturing Company

Construction Company

17%

Outsourcing Company

10%

Financial Services Firm

Computer Software Company

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	11
Midsize Enterprise	13
Large Enterprise	23

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 is your experience regarding pricing and costs for Snowflake Analytics?

The pricing for Snowflake Analytics is reasonable, but as I am not part of the management team, I am not certain about our organization's exact costs. Overall, the return on investment for this too...

See all answers

What needs improvement with Snowflake Analytics?

One improvement Snowflake Analytics could benefit from is in cost, particularly during peak hours. Sometimes, due to its automatic scalability, we think it has scaled up, but it does not always hap...

See all answers

What is your primary use case for Snowflake Analytics?

I am using Snowflake Analytics because we are already using Snowflake for data engineering and data warehousing tasks, and we are using it for analytics as well as business intelligence reporting. ...

See all answers

Comparisons

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Compared 10% of the time

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Compared 9% of the time

Keen IO vs Snowflake Analytics

Compared 6% of the time

Firebolt vs Snowflake Analytics

Compared 5% of the time

Azure Data Factory vs Snowflake Analytics

Compared 5% of the time

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Product Reports

Buyer's Guide

Microsoft Parallel Data Warehouse

August 2026

Microsoft Parallel Data Warehouse report

Download Microsoft Parallel Data Warehouse product report

Buyer's Guide

Snowflake Analytics

July 2026

Download Snowflake Analytics product report

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

Snowflake Analytics offers advanced capabilities in data warehousing and cloud data migration, with support for machine learning and business intelligence tasks. Its scalable architecture supports large data volumes while enhancing cost efficiency through decoupled computation and storage.

As a flexible, managed environment, Snowflake Analytics enhances data sharing and integration across multiple cloud platforms. It allows seamless data pipeline creation, supports advanced analytics, and facilitates reporting and visualization. Despite facing integration challenges with legacy systems and complex queries, Snowflake's continuous improvements aim to address these issues, making it a reliable choice for organizations transitioning to the cloud.

What features define Snowflake Analytics?

Time Travel: Enables users to access historical data effortlessly.
Zero-Copy Cloning: Allows cloning of data without storage costs.
Scalability: Easily handles large data volumes.
Data Sharing: Facilitates seamless data sharing across platforms.
Decoupled Architecture: Enhances cost efficiency by separating computation and storage.

What benefits should businesses look for in Snowflake reviews?

Cost Efficiency: Optimized costs through advanced storage management.
Performance: High-speed computations and real-time analytics.
Security: End-to-end encryption ensuring data security.
Flexibility: Supports multiple cloud environments for diverse needs.

Enterprises across industries utilize Snowflake Analytics for its robust data handling and cloud integration capabilities. It serves sectors in need of efficient data warehousing, real-time analytics, and machine learning support, making it suitable for cloud migration and enhancing business intelligence operations.

Snowflake Computing

Sample Customers

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

Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse. Updated: August 2026.

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