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Microsoft Azure Synapse Analytics vs Snowflake vs Teradata 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
6.4
Microsoft Azure Synapse Analytics provides cost savings and efficiency with serverless options, achieving up to 70% ROI in years.
Sentiment score
6.8
Snowflake users praise its scalability and ease of use, though financial gains vary and may require longer usage periods.
Sentiment score
8.1
Teradata boosts speed and ROI, with high customer satisfaction and enhanced analytics, rated highly by organizations like Central Bank of Colombia.
Some of my customers have indeed seen a return on investment with Microsoft Azure Synapse Analytics as they used it for analytics to drive decision-making, improving their processes or increasing revenue.
We have realized a return on investment, with a reduction of staff from 27 to eight, and our current return on investment is approximately 14%.
 

Customer Service

Sentiment score
6.6
Microsoft Azure Synapse Analytics support is knowledgeable but experiences vary; users praise extensive documentation for self-resolving issues.
Sentiment score
5.7
Snowflake support is responsive and helpful, with high user satisfaction, despite occasional slower response times and ticketing reliance.
Sentiment score
7.1
Teradata's customer service is highly rated for professionalism and expertise, though response times occasionally need improvement and experiences vary.
They are slow to respond and not very knowledgeable.
This is an underestimation of the real impact because we use big data also to monitor the network and the customer.
I would rate the support for Microsoft Azure Synapse Analytics as an eight out of ten.
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.
The customer support for Teradata has been great.
Customer support is very good, rated eight out of ten under our essential agreement.
The technical support from Teradata is quite advanced.
 

Scalability Issues

Sentiment score
7.5
Microsoft Azure Synapse Analytics offers scalable solutions with serverless architecture, appreciated for flexibility and adaptability despite potential costs.
Sentiment score
7.8
Snowflake offers excellent scalability, adaptable to varying needs, with minimal challenges but requires cost and resource management attention.
Sentiment score
7.4
Teradata's cloud capabilities offer flexible, efficient scalability, though some users face cost and on-premise expansion challenges.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework.
Recovering from such scenarios becomes a bit problematic or time-consuming.
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.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
Teradata's scalability is great; it's been awesome.
 

Stability Issues

Sentiment score
7.5
Microsoft Azure Synapse Analytics is reliable and efficient, with high user satisfaction despite occasional issues with large datasets.
Sentiment score
8.2
Snowflake offers high stability and reliability with minimal downtime, rapid recovery, and seamless failover across platforms, especially AWS.
Sentiment score
8.3
Teradata is praised for stability with high uptime, robust architecture, minimal downtime, and effective workload management despite occasional issues.
I find the service stable as I have not encountered many issues.
We have never integrated Microsoft Azure Synapse Analytics with Databricks, but we have mostly pulled data from on-premises systems into Azure Databricks.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
 

Room For Improvement

Microsoft Azure Synapse Analytics users seek better integration, performance, simpler interfaces, affordability, and expanded support for IoT and machine learning.
Snowflake needs interface improvements, better ETL, machine learning features, pricing clarity, advanced tools, and enhanced documentation and security.
Teradata needs improvements in transactional processing, user interface, pricing, integration, analytics, scalability, AI features, and support.
There is a need for better documentation, particularly for customized tasks with Microsoft Azure Synapse Analytics.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
The reasons I don't rate Microsoft Azure Synapse Analytics higher include data integration and tech support being two main issues.
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.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.
 

Setup Cost

Microsoft Azure Synapse Analytics offers flexible, costly pay-as-you-go pricing, suiting medium to large enterprises with substantial data needs.
Snowflake offers competitive pay-as-you-go pricing with some concerns over transparency, predictability, and potential cost escalation.
Teradata's high pricing is justified by performance, with flexible models offering value for large projects, requiring negotiation.
The cheapest tier costs about $4,000 to $4,700 a year, while the most expensive tier can reach up to $300,000 a year.
I think the price of Microsoft Azure Synapse Analytics is very expensive, but that's not only for Microsoft Azure Synapse Analytics—it's for the cloud in general.
I find the pricing of Microsoft Azure Synapse Analytics reasonable.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
We spent roughly $295,000 on setup costs.
 

Valuable Features

Microsoft Azure Synapse Analytics provides scalable, secure data processing with seamless integration, user-friendly operations, and Power BI compatibility.
Snowflake excels in scalability, efficiency, ease of use, AI/ML capabilities, security, and seamless third-party integration, enhancing user experience.
Teradata offers scalable, fast processing with excellent performance, adaptability, ease of use, robust security, and advanced analytics capabilities.
One of the most valuable features in Microsoft Azure Synapse Analytics is the ability to write your own ETL code using Azure Data Factory, which is a component within Synapse.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
The independence of the compute and storage within Snowflake is key.
Teradata's security helps our organization meet compliance requirements such as GDPR and IFRS, and it is particularly essential for revenue contracting or revenue recognition.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
 

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 6.3%, down from 7.5% compared to the previous year. The mindshare of Snowflake is 17.7%, down from 22.9% compared to the previous year. The mindshare of Teradata is 8.5%, down from 9.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Snowflake17.7%
Teradata8.5%
Microsoft Azure Synapse Analytics6.3%
Other67.5%
Cloud Data Warehouse
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Has supported data pipeline development but still requires better integration and support
The best feature of Microsoft Azure Synapse Analytics is the notebook functionality; it provides a very good interface, and we can easily do our experiments, POCs, and check things before migration or deployment to higher environments such as from development to SIT and then production. The deployment process is also much smoother. Driving data-driven insights in my organization depends upon the preparation of the data. If your data is not good, then insights won't be good, and Microsoft Azure Synapse Analytics helps in preparing your data, so it is very helpful. I find Microsoft Azure Synapse Analytics' native data lake support beneficial.
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.
Kirk Robinson - PeerSpot reviewer
Has improved data quality, optimized reporting processes, and enabled predictive insights across business units
The limitation we encountered was related to speed, prompting us to increase our AWS cloud thresholds and benchmarks on the servers, adding more throughput. We have been testing that, but speed remains one of our key issues. The integration has been awesome because of the platforms and their usage, and usability is great. The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts. If Teradata could provide a list of certified experts, that would be fantastic. I rated Teradata a nine because the main area for improvement is the bandwidth of resources that could assist us in applying to our projects, specifically more certified and expert resources. The market share of Teradata professionals is limited, creating an issue for us.
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Comparison Review

it_user232068 - PeerSpot reviewer
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Top Industries

By visitors reading reviews
Manufacturing Company
12%
Financial Services Firm
8%
Computer Software Company
7%
Government
6%
Financial Services Firm
19%
Computer Software Company
12%
Manufacturing Company
8%
Healthcare Company
6%
Financial Services Firm
25%
Computer Software Company
9%
Manufacturing Company
8%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business29
Midsize Enterprise18
Large Enterprise55
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise20
Large Enterprise56
By reviewers
Company SizeCount
Small Business26
Midsize Enterprise12
Large Enterprise49
 

Questions from the Community

How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?
Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very str...
What do you like most about Microsoft Azure Synapse Analytics?
The product is easy to use, and anybody can easily migrate to advanced DB.
What is your experience regarding pricing and costs for Microsoft Azure Synapse Analytics?
I find the pricing of Microsoft Azure Synapse Analytics reasonable; compared to AWS Glue or Databricks, it is reasona...
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 Databric...
What needs improvement with Snowflake?
Pricing is quite high for Snowflake Data Cloud, which is an area that could be improved. Snowflake Data Cloud is stil...
Comparing Teradata and Oracle Database, which product do you think is better and why?
I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may d...
Which companies use Teradata and who is it most suitable for?
Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if ...
Is Teradata a difficult solution to work with?
Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if ...
 

Also Known As

Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
Snowflake Computing, Snowflake Data Cloud
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture, Teradata Vantage Enterprise (DIY)
 

Overview

 

Sample Customers

Toshiba, Carnival, LG Electronics, Jet.com, Adobe, 
Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Netflix
Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse. Updated: October 2025.
868,787 professionals have used our research since 2012.