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Apache Hadoop vs Microsoft Azure Synapse Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 27, 2025

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
5.4
Apache Hadoop offers cost-effective storage and processing, benefiting some with analytics and optimizing data applications for resource savings.
Sentiment score
6.4
Microsoft Azure Synapse Analytics offers cost savings, simplified management, and flexible serverless options, enhancing overall returns and efficiency.
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.
 

Customer Service

Sentiment score
6.1
Customer service for Apache Hadoop varies, with differing satisfaction levels and reliance on external resources and forums for support.
Sentiment score
6.6
Opinions on Azure Synapse Analytics support vary, with mixed feedback on responsiveness, expertise, and communication, yet documentation is praised.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
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.
 

Scalability Issues

Sentiment score
7.4
Apache Hadoop is valued for its scalability, supporting large data and users effectively, especially in cloud environments.
Sentiment score
7.5
Microsoft Azure Synapse Analytics is praised for seamless scalability and adaptability, despite some complex data challenges, across industries.
It is a distributed file system and scales reasonably well as long as it is given sufficient resources.
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.
 

Stability Issues

Sentiment score
7.1
Apache Hadoop is stable and reliable in multi-node clusters, performing well with minimal instability during high-load operations.
Sentiment score
7.5
Microsoft Azure Synapse Analytics is praised for stability and performance, with users rating it highly despite minor glitches.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
Performance and stability are absolutely fine because Microsoft Azure Synapse Analytics is a PaaS service.
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.
 

Room For Improvement

Apache Hadoop needs user-friendly enhancements, better integration, improved security, streamlined setup, and modernized features and support.
Users want improved Azure Synapse integration, ease of use, scalability, documentation, security, IoT support, and better monitoring.
The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it.
Microsoft Azure Synapse Analytics is an excellent product because it includes both SIEM and orchestration capabilities with playbooks.
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.
 

Setup Cost

Enterprise Apache Hadoop pricing varies greatly, influenced by distribution choice, deployment type, and specific usage requirements.
Azure Synapse Analytics offers variable pricing, starting from €1,000, influenced by usage, compute power, and storage consumption.
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.
 

Valuable Features

Apache Hadoop offers scalable, cost-effective data processing, supporting diverse environments with fault tolerance, integration, and analytics tools like Hive.
Microsoft Azure Synapse Analytics offers scalable data processing, seamless integration, and cost-efficient analytics in a user-friendly environment.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
I assess Apache Hadoop's fault tolerance during hardware failures positively since we have hardware failover, which works without problems.
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.
 

Categories and Ranking

Apache Hadoop
Average Rating
8.0
Reviews Sentiment
6.6
Number of Reviews
41
Ranking in other categories
Data Warehouse (6th)
Microsoft Azure Synapse Ana...
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
97
Ranking in other categories
Cloud Data Warehouse (5th)
 

Featured Reviews

Sushil Arya - PeerSpot reviewer
Provides ease of integration with the IT workflow of a business
When working with Kafka, I saw that the data came in an incremental order. The incremental data processing part is still not very effective in Apache Hadoop. If the data is already there, it can be processed very effectively, especially if the data is coming in every second. If you want to know the location of some data every second, then such data is not processed effectively in Apache Hadoop. I can say that one of the features where improvements are required revolves around the licensing cost of the tool. If the tool can build some licensing structures in a pay-per-use manner, organizations can get the look and feel of Apache Hadoop. Apache Hadoop can offer a licensing structure of the product that can be seen as similar to how AWS operates. Apache Hadoop can look into the capability of processing incremental data. The tool's setup process can be a scope of improvement. Also, it is not very simple because while doing the setup, we need to do all the server settings, including port listing and firewall configurations. If we look at other products on the market, then they can be made simpler. There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required. The time frame for the resolution is an area that needs to be improved. The overall communication part of the technical support team also needs improvement.
AnandTiwari - PeerSpot reviewer
Has consistently supported integration across diverse environments and streamlined deployment processes
Microsoft Azure Synapse Analytics could improve their pricing structure. They currently have two separate pricing tiers: full log and partial log. I suggest they implement a single price and reduce charges on logs. They could implement a cap with some free tier or price tier based on the GBs of log collected. This would help customers use Azure more effectively. Microsoft Azure Synapse Analytics is an excellent product because it includes both SIEM and orchestration capabilities with playbooks, but the log management part is very costly. Regarding future improvements, I would appreciate more application connectors for integration, particularly for on-premise based solutions. Many customers still maintain on-premise infrastructure, so having more integration possibilities for these environments would be beneficial.
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Top Industries

By visitors reading reviews
Financial Services Firm
35%
Computer Software Company
10%
University
6%
Government
4%
Manufacturing Company
12%
Financial Services Firm
8%
Computer Software Company
7%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business14
Midsize Enterprise8
Large Enterprise21
By reviewers
Company SizeCount
Small Business29
Midsize Enterprise18
Large Enterprise55
 

Questions from the Community

What do you like most about Apache Hadoop?
It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.
What is your experience regarding pricing and costs for Apache Hadoop?
The product is open-source, but some associated licensing fees depend on the subscription level. While it might be free for students, organizations typically need to pay for their subscriptions. Th...
What needs improvement with Apache Hadoop?
The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it. This wa...
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 straightforward. This solution can merge and integrate well with many different dat...
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 reasonable.
 

Also Known As

No data available
Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
Toshiba, Carnival, LG Electronics, Jet.com, Adobe, 
Find out what your peers are saying about Apache Hadoop vs. Microsoft Azure Synapse Analytics and other solutions. Updated: September 2025.
869,952 professionals have used our research since 2012.