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Apache Hadoop vs Microsoft Azure Synapse Analytics comparison

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Executive Summary
Updated on July 11, 2022

We performed a comparison between Apache Hadoop and Microsoft Azure Synapse Analytics based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.

  • Ease of Deployment: Some users of both solutions say that their initial setup is straightforward, while others feel it is complex.
  • Features: Users of both products are happy with their stability and scalability.

    Hadoop users praise its distributed processing and say it is reliable but difficult to configure. Synapse users say it is user friendly and has good integration options but needs better encryption capabilities.
  • Pricing: Hadoop reviewers say that it is an expensive solution. In contrast, most Synapse reviewers feel that it is fairly priced.
  • Service and Support: Reviewers of both solutions report being satisfied with the level of support they receive.

Comparison Results: Synapse has a slight edge in this comparison. According to its users, it is more user-friendly and less expensive than Hadoop.

To learn more, read our detailed Apache Hadoop vs. Microsoft Azure Synapse Analytics report (Updated: July 2022).
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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"We selected Apache Hadoop because it is not dependent on third-party vendors.""The scalability of Apache Hadoop is very good.""The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable.""What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies.""The performance is pretty good.""Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability.""Hadoop is extensible — it's elastic."

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"The architecture, including compute and storage, is good.""Fills the gap between big data and classic data warehouses.""The features most valuable are the simplicity, how easy it is to create a dashboard from different information systems.""One of the most valuable features of this solution is its ability to integrate well with other services offered by Azure.""It's scalable; you can scale up and scale down.""The product is very user friendly.""I have not used the technical support from Microsoft Azure Synapse Analytics, but I worked with the developers at Microsoft who were top-notch.""The most important feature for me is the integration with PolyBase."

More Microsoft Azure Synapse Analytics Pros →

Cons
"Real-time data processing is weak. This solution is very difficult to run and implement.""It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it.""The integration with Apache Hadoop with lots of different techniques within your business can be a challenge.""What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly.""Hadoop's security could be better.""From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective.""The solution is very expensive."

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"It would be ideal if the solution could be better used intuitively by the staff without having a great deal of training.""It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft.""The initial setup is complex.""We'd, of course, always like to pay less for the service if we can.""Synapse Analytics is generally stable, but its performance can be slow when performing very large datasets.""Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better.""The only concern for us is the cost part. When it comes to the implementation and the support and maintenance, we see high-cost implications.""If I'm looking for something good in the cloud, I would want it to have better standard connectors."

More Microsoft Azure Synapse Analytics Cons →

Pricing and Cost Advice
  • "The price of Apache Hadoop could be less expensive."
  • "If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during storage, for example, though I don't know exactly how much Apache Hadoop costs."
  • "We don't directly pay for it. Our clients pay for it, and they usually don't complain about the price. So, it is probably acceptable."
  • More Apache Hadoop Pricing and Cost Advice →

  • "Our license is very expensive"
  • "They are cost aggressive, and it integrates well with other Microsoft tools."
  • "There is a cost calculator available online that allows you to input your entire scenario, and it will get back to you with information on what the costs are going to be."
  • "Its price could be better. It was a school project, and I got it for free. If I try to pay through my company, it is a little bit more expensive as compared to Oracle."
  • "The price of the package not expensive and depends on how much it is used."
  • "The cost of the licensing depends on the size of the warehouse, where the cost of storage is approximately $130 USD per terabyte."
  • "This is a cost-effective product."
  • "Because it's cloud the cost is a different convention and the licensing costs are not the same."
  • More Microsoft Azure Synapse Analytics Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:I don't think using Apache Spark without Hadoop has any major drawbacks or issues. I have used Apache Spark quite successfully with AWS S3 on many projects which are batch based. Yes for very high… more »
    Top Answer:What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some… more »
    Top Answer:If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during… more »
    Top Answer: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… more »
    Top Answer:Traditional ETL would usually use a dedicated database (or even database server) where you'll load & transform your raw data before ingesting it into the final destination. This would allow checking… more »
    Ranking
    6th
    out of 30 in Data Warehouse
    Views
    6,020
    Comparisons
    5,249
    Reviews
    6
    Average Words per Review
    437
    Rating
    7.5
    2nd
    Views
    33,074
    Comparisons
    22,599
    Reviews
    44
    Average Words per Review
    491
    Rating
    7.9
    Comparisons
    Also Known As
    Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
    Learn More
    Overview
    The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

    Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.

    Microsoft Azure Synapse Analytics is built with these 4 components:

    1. Synapse SQL
    2. Spark
    3. Synapse Pipeline
    4. Studio

    Microsoft Azure Synapse Analytics Features

    Microsoft Azure Synapse Analytics has many valuable key features, including:

    • Cloud Data Service: WIth Microsoft Azure Synapse Analytics you can operate services (data analytics, machine learning, data warehousing, dashboarding, etc.) in a single workspace via the cloud.

    • Structured and unstructured data: Microsoft Azure Synapse Analytics supports both structured and unstructured data and allows you to manage relational and non-relational data - unlike data warehouses and lakes that tend to store them respectively.

    • Effective data storage: Microsoft Azure Synapse Analytics offers next-level data storage with high availability and different tiers.

    • Responsive data engine: Microsoft Azure Synapse Analytics uses Massive Parallel Processing (MPP) and is designed to handle large volumes of data and analytical workloads efficiently without any problems.

    • Several scripting languages: The solution provides language compatibility and supports different programming languages, such as Python, Java, Spark SQL, and Scala.

    • Query optimization: Microsoft Azure Synapse Analytics works well to facilitate limitless concurrency and performance optimization. It also simplifies workload management.

    Microsoft Azure Synapse Analytics Benefits

    Some of the benefits of using Microsoft Azure Synapse Analytics include:

    • Database templates: Microsoft Azure Synapse Analytics offers industry-specific database templates that make it easy to combine and shape data.

    • Better business insights: With Microsoft Azure Synapse Analytics you can expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.

    • Reduce project development time: Microsoft Azure Synapse Analytics makes it possible to have a unified experience for developing end-to-end analytics, which reduces project development time significantly.

    • Eliminate data barriers: By using Microsoft Azure Synapse Analytics, you can perform analytics on operational and business apps data without data movement.

    • Advanced security: Microsoft Azure Synapse Analytics provides both advanced security and privacy features to ensure data protection.

    • Machine Learning: Microsoft Azure Synapse Analytics integrates Azure Machine Learning, Azure Cognitive Services, and Power BI.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.

    PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."

    Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

    A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."


    Offer
    Learn more about Apache Hadoop
    Learn more about Microsoft Azure Synapse Analytics
    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, 
    Top Industries
    REVIEWERS
    Comms Service Provider40%
    Financial Services Firm40%
    Consumer Goods Company10%
    Government10%
    VISITORS READING REVIEWS
    Computer Software Company24%
    Comms Service Provider17%
    Financial Services Firm15%
    Energy/Utilities Company5%
    REVIEWERS
    Computer Software Company24%
    Comms Service Provider14%
    Manufacturing Company10%
    Healthcare Company10%
    VISITORS READING REVIEWS
    Computer Software Company25%
    Comms Service Provider16%
    Financial Services Firm7%
    Energy/Utilities Company6%
    Company Size
    REVIEWERS
    Small Business32%
    Midsize Enterprise28%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise14%
    Large Enterprise72%
    REVIEWERS
    Small Business27%
    Midsize Enterprise24%
    Large Enterprise49%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise15%
    Large Enterprise67%
    Buyer's Guide
    Data Warehouse
    July 2022
    Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse. Updated: July 2022.
    621,703 professionals have used our research since 2012.

    Apache Hadoop is ranked 6th in Data Warehouse with 7 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 44 reviews. Apache Hadoop is rated 7.8, while Microsoft Azure Synapse Analytics is rated 7.8. The top reviewer of Apache Hadoop writes "Has good processing power and speed and is capable of handling large volumes of data and doing online analysis". On the other hand, the top reviewer of Microsoft Azure Synapse Analytics writes "Scalable, intuitive, facilitates compliance and keeping your data secure". Apache Hadoop is most compared with Snowflake, Oracle Exadata, VMware Tanzu Greenplum, Azure Data Factory and Teradata, whereas Microsoft Azure Synapse Analytics is most compared with Snowflake, Amazon Redshift, Azure Data Factory, SAP BW4HANA and Oracle Autonomous Data Warehouse.

    We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.