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Apache Hadoop vs Microsoft Azure Synapse Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 12, 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
6.5
Apache Hadoop provides cost-effective data storage and processing, though ROI varies based on analytics use and sophistication.
Sentiment score
7.0
Users experienced positive ROI with Azure Synapse, citing cost reductions, improved data efficiency, and flexibility over traditional solutions.
 

Customer Service

Sentiment score
6.4
Customer service varies by Hadoop distributor, with Hortonworks rated highly; support depends on vendor, community resources, or external vendors.
Sentiment score
6.9
Microsoft Azure Synapse Analytics support quality varies; larger accounts receive better service, but smaller customers experience challenges.
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.
 

Scalability Issues

Sentiment score
7.6
Apache Hadoop excels in scalability, allowing easy cluster expansion and efficient data handling, ideal for varied organizational needs.
Sentiment score
7.7
Microsoft Azure Synapse Analytics offers high scalability, enabling easy scaling for diverse industries despite potential high costs.
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.
 

Stability Issues

Sentiment score
7.3
Apache Hadoop's stability, rated 8/10, improves with newer versions, though minor issues exist with memory and data processing.
Sentiment score
7.6
Microsoft Azure Synapse Analytics is stable, commendable in performance, but some users desire improvements for large data handling reliability.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
I find the service stable as I have not encountered many issues.
 

Room For Improvement

Apache Hadoop needs improved usability, integration, security, support, and performance for efficient high-volume data processing and better community resources.
Microsoft Azure Synapse Analytics needs improvements in pricing, usability, integration, performance, and advanced features for enhanced overall functionality.
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.
There is a need for more expertise among the support team to guide us effectively.
 

Setup Cost

Enterprise Hadoop offers cost benefits but varies with deployment type and distribution, impacting smaller organizations more heavily.
Enterprise users of Azure Synapse Analytics find pricing variable, ranging from affordable to expensive, with concerns over billing unpredictability.
 

Valuable Features

Apache Hadoop excels with a scalable, cost-effective system handling diverse data types, integrating with tools, and supporting big data analytics.
Microsoft Azure Synapse Analytics offers scalability, seamless integration, user-friendly design, robust security, and efficient data processing for businesses.
Hadoop is a distributed file system, and it scales reasonably well provided you give it sufficient resources.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
 

Categories and Ranking

Apache Hadoop
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
40
Ranking in other categories
Data Warehouse (7th)
Microsoft Azure Synapse Ana...
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
92
Ranking in other categories
Cloud Data Warehouse (2nd)
 

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.
Renee Hoon - PeerSpot reviewer
Scalable performance tuning and optimization for finance and supply chain jobs
We run our finance and supply chain jobs using SQL BW, and we visualize our data loads on Power BI. We are using SQL Data Warehouse for data warehousing In terms of cost savings, we don't need specialization in skills as advanced as Teradata. We used to pay extensive licensing fees for Teradata,…
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Top Industries

By visitors reading reviews
Financial Services Firm
34%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Educational Organization
52%
Computer Software Company
5%
Manufacturing Company
5%
Financial Services Firm
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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?
Hadoop lacks OLAP capabilities. I recommend adding a Delta Lake feature to make the data compatible with ACID properties. Also, video and audio streaming import issues could be improved to ensure p...
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?
We use an enterprise-level subscription for Microsoft Azure Synapse Analytics. I would rate our satisfaction with the price around five, as I have not focused much on cost aspects presently.
 

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: February 2025.
845,406 professionals have used our research since 2012.