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Microsoft Parallel Data Warehouse vs Snowflake comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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
6.9
Most are satisfied with ROI, acknowledging its benefits, though improvements are possible, as it efficiently enhances backend operations.
Sentiment score
6.8
Snowflake users experience mixed ROI; challenges in calculation exist, but long-term benefits include cost reduction and improved data management.
 

Customer Service

Sentiment score
6.8
Microsoft Parallel Data Warehouse support is responsive and expert, though users sometimes need online resources for faster solutions.
Sentiment score
5.7
Snowflake's customer service is praised for expertise and helpfulness, though some note delays and lack of SLAs.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
The technical support from Snowflake is very good, nice, and efficient.
 

Scalability Issues

Sentiment score
7.2
Microsoft Parallel Data Warehouse excels in scalability, integration, and expandability, though improvements are needed for large data sets.
Sentiment score
7.8
Snowflake is praised for scalability and efficiency, but concerns exist regarding cost-effectiveness in medium to large-scale organizations.
I give the scalability an eight out of ten, indicating it scales well for our needs.
As a consultant, we hire additional programmers when we need to scale up certain major projects.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
 

Stability Issues

Sentiment score
8.0
Microsoft Parallel Data Warehouse is praised for its stability, reliability, and quick issue resolution, despite time-consuming extensive dataset processing.
Sentiment score
8.2
Snowflake is praised for stability and reliability, with users noting excellent performance, quick issue resolution, and robust architecture.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
 

Room For Improvement

Microsoft Parallel Data Warehouse presents complexity, compatibility challenges, performance issues, high costs, and requires improved in-memory analysis and updates.
Snowflake users seek improved UI, pricing transparency, analytics, integrations, AI features, and enhanced support, ETL, and machine learning capabilities.
It would be better to release patches less frequently, maybe once a month or once every two months.
When there are many users or many expensive queries, it can be very slow.
The ETL designing process could be optimized for better efficiency.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
Cost reduction is one area I would like Snowflake to improve.
 

Setup Cost

Microsoft Parallel Data Warehouse's pricing varies by needs; Azure integration can be cost-effective, but technical support costs extra.
Snowflake's pricing offers flexibility but can be unpredictable and expensive compared to Redshift or BigQuery, with room for transparency improvements.
Microsoft Parallel Data Warehouse is very expensive.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
 

Valuable Features

Microsoft Parallel Data Warehouse offers performance, integration, flexibility, and cost-effectiveness for large data management and business intelligence.
Snowflake excels in scalable, secure data processing with fast queries, multi-format support, and seamless third-party integration for AI/ML.
The columnstore index enhances data query performance by using less space and achieving faster performance than general indexing.
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.
Microsoft Parallel Data Warehouse is used in the logistics area for optimizing SQL queries related to the loading and unloading of trucks.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
Being able to perform AI and Machine Learning in the same location as the data is quite advantageous.
 

Categories and Ranking

Microsoft Parallel Data War...
Ranking in Data Warehouse
10th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
38
Ranking in other categories
No ranking in other categories
Snowflake
Ranking in Data Warehouse
1st
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
100
Ranking in other categories
Cloud Data Warehouse (1st), AI Synthetic Data (1st)
 

Mindshare comparison

As of July 2025, in the Data Warehouse category, the mindshare of Microsoft Parallel Data Warehouse is 1.1%, down from 1.1% compared to the previous year. The mindshare of Snowflake is 14.0%, down from 19.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
 

Featured Reviews

Ashok Bhadra - PeerSpot reviewer
Provides flexible data handling and integrates easily but requires less frequent patch releases
Microsoft Parallel Data Warehouse keeps giving updates and new features. In my first consultancy, I transitioned a mortgage company from Oracle OBIEE to Microsoft Parallel Data Warehouse to greatly reduce the mortgage approval time. 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. It extracts data from the ERP system, and we are doing extensive data analytics. The system handles target marketing for a company which does 85 to 90% of its business in wholesale. We have a variety of clients from mom-and-pop stores to big box stores, and we have intermediaries. We sell through approximately 13 retail channels including Etsy, our retail website, Faire, Wayfair, and Walmart. Each channel requires different types of inventory updates and packaging, which is managed automatically. A significant amount of development is done on Microsoft Parallel Data Warehouse where all these processes are automatically fed out and updated. We also conduct inventory analysis and aging analysis. We identify seasonal buyers, track their purchasing habits, and auto-trigger campaigns for them, sometimes offering discounts on various items. We've found that combining top-selling items with non-selling items can lead to increased sales, as people often buy additional items when they find one on sale.
Snehasish Das - PeerSpot reviewer
Transformation in data querying speed with good migration capabilities
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses. One key feature is the separation of compute and storage, which eliminates storage limitations. It also has tools for migrating data from legacy databases like Oracle. Its stability and efficiency enhance performance greatly. Tools in the AI/ML marketplace are readily available without needing development.
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Top Industries

By visitors reading reviews
Computer Software Company
28%
Financial Services Firm
15%
Insurance Company
10%
University
7%
Financial Services Firm
19%
Educational Organization
14%
Computer Software Company
11%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Microsoft Parallel Data Warehouse?
Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time.
What needs improvement with Microsoft Parallel Data Warehouse?
Microsoft Parallel Data Warehouse is excellent but very expensive. Working on the pricing could make it a better solution.
What do you like most about Snowflake?
The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power.
What is your experience regarding pricing and costs for Snowflake?
It is complicated to understand how requests impact warehouse size. Unlike competitors such as Microsoft and Databricks ( /products/databricks-reviews ), Snowflake lacks transparency in estimating ...
What needs improvement with Snowflake?
There is a need for a tool to help me estimate the cost of using Snowflake. Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently r...
 

Also Known As

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

Overview

 

Sample Customers

Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel Europe
Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Snowflake and other solutions. Updated: May 2025.
860,592 professionals have used our research since 2012.