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Microsoft Parallel Data Warehouse vs Snowflake Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

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
6.6
Snowflake Analytics offers potential 40-50% performance benefits and cost savings, though financial returns vary based on user needs.
 

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
7.0
Snowflake Analytics receives praise for responsive support, though some suggest improvements in complex issue resolution and occasional delay handling.
The technical support for Snowflake Analytics is excellent based on what I have heard from others.
 

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
8.0
Snowflake Analytics efficiently manages large data volumes with dynamic cloud scaling, offering superior scalability and cost efficiency versus competitors.
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.
It supports both horizontal and vertical scaling effectively.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
 

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
8.5
Snowflake Analytics is highly rated for its stable and reliable performance, ensuring minimal disruptions and high availability.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
Snowflake Analytics is stable, scoring around eight point five to nine out of ten.
 

Room For Improvement

Microsoft Parallel Data Warehouse presents complexity, compatibility challenges, performance issues, high costs, and requires improved in-memory analysis and updates.
Snowflake Analytics needs improved integration, machine learning, speed, user interface, cost transparency, data handling, and real-time support.
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.
If it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better.
AIML-based SQL prompt and query generation could be an area for enhancement.
Navigating the user console can be challenging, particularly when looking for details like the account ID.
 

Setup Cost

Microsoft Parallel Data Warehouse's pricing varies by needs; Azure integration can be cost-effective, but technical support costs extra.
Snowflake Analytics offers flexible, region-dependent pricing, deemed costly by some but competitive due to its ease and flexibility.
Microsoft Parallel Data Warehouse is very expensive.
Snowflake Analytics is quite economical.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
 

Valuable Features

Microsoft Parallel Data Warehouse offers performance, integration, flexibility, and cost-effectiveness for large data management and business intelligence.
Snowflake Analytics provides efficient, secure, and scalable data management, supporting seamless integration and cost-effective analytics with advanced features.
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 Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.
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.
It is a data offering where I can see data lineage, data governance, and data security.
 

Categories and Ranking

Microsoft Parallel Data War...
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
38
Ranking in other categories
Data Warehouse (10th)
Snowflake Analytics
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
40
Ranking in other categories
Web Analytics (1st), Cloud Data Warehouse (9th)
 

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.
Paresh_Nayak - PeerSpot reviewer
Enables data-driven decision-making with robust features and effective scalability
The internal design engine and the columnar database are particularly valuable. These features reduce input and output memory, which is crucial in handling large data sets. The solution fulfills the business requirement for scaling and analytics. Snowflake Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.
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Top Industries

By visitors reading reviews
Computer Software Company
25%
Insurance Company
12%
Financial Services Firm
8%
University
8%
Computer Software Company
15%
Financial Services Firm
10%
Retailer
10%
Insurance Company
6%
 

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?
The patch releases are a concern. For a customer with tons of servers, frequent patches lead to required reboots, which interrupts business. It would be better to release patches less frequently, m...
What is your experience regarding pricing and costs for Snowflake Analytics?
Snowflake Analytics is quite economical. It does not appear to incur significant extra expenses beyond the solution's initial cost. However, a complete pricing analysis is still in progress.
What needs improvement with Snowflake Analytics?
The advantages of Snowflake Analytics outweigh the disadvantages. However, if it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it wo...
 

Also Known As

Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data Warehouse, MS Parallel Data Warehouse
No data available
 

Overview

 

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 Microsoft Parallel Data Warehouse vs. Snowflake Analytics and other solutions. Updated: July 2025.
865,384 professionals have used our research since 2012.