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Apache Hadoop vs Microsoft Azure Synapse Analytics comparison

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Data Warehouse
June 2022
Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse. Updated: June 2022.
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Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Hadoop is extensible — it's elastic.""The performance is pretty good.""The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so.""Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability.""The scalability of Apache Hadoop is very good.""We selected Apache Hadoop because it is not dependent on third-party vendors."

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"Can capture all the transactional data throughout a company.""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.""The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit.""This is a stable solution with many functionalities.""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 ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage.""The pricing seems to be quite fair.""I have been working with Microsoft, and they have been very helpful."

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Cons
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge.""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 needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning.""The solution is very expensive.""Real-time data processing is weak. This solution is very difficult to run and implement."

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"While the solution is flexible, sometimes this works against the user.""If I'm looking for something good in the cloud, I would want it to have better standard connectors.""I am pretty sure that there are areas that need improvement but I just can think of them off the top of my head.""We'd, of course, always like to pay less for the service if we can.""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 major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse. There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process. When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.""Microsoft Azure Synapse Analytics could improve its compatibility with Visual Studio. One of the challenges for people moving from an on-premise to a cloud solution, such as Microsoft Azure Synapse Analytics, is that you're constantly working in a browser. There are people that have been working for decades on desktop applications. For them to start working in a browser, it's quite a change. Allowing people to work and do their work inside Visual Studio than in the browser, would be a large advantage.""When I was trying to link services to an SFTP site it was not able to do all the possible encryption that I needed. They can improve by adding more encryption options."

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Pricing and Cost Advice
  • "The price of Apache Hadoop could be less expensive."
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  • "All of the prices are available online."
  • "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."
  • 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:The scalability of Apache Hadoop is very good.
    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
    6,063
    Comparisons
    5,274
    Reviews
    6
    Average Words per Review
    446
    Rating
    7.7
    2nd
    Views
    31,104
    Comparisons
    21,912
    Reviews
    39
    Average Words per Review
    502
    Rating
    7.8
    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
    Financial Services Firm50%
    Comms Service Provider25%
    Consumer Goods Company13%
    Government13%
    VISITORS READING REVIEWS
    Computer Software Company26%
    Comms Service Provider15%
    Financial Services Firm15%
    Energy/Utilities Company5%
    REVIEWERS
    Computer Software Company27%
    Healthcare Company12%
    Comms Service Provider12%
    Insurance Company8%
    VISITORS READING REVIEWS
    Computer Software Company26%
    Comms Service Provider15%
    Financial Services Firm7%
    Energy/Utilities Company6%
    Company Size
    REVIEWERS
    Small Business36%
    Midsize Enterprise27%
    Large Enterprise36%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise14%
    Large Enterprise72%
    REVIEWERS
    Small Business29%
    Midsize Enterprise22%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise15%
    Large Enterprise68%
    Buyer's Guide
    Data Warehouse
    June 2022
    Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse. Updated: June 2022.
    608,010 professionals have used our research since 2012.

    Apache Hadoop is ranked 6th in Data Warehouse with 6 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 43 reviews. Apache Hadoop is rated 7.6, while Microsoft Azure Synapse Analytics is rated 7.8. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". 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, SAP BW4HANA, Oracle Autonomous Data Warehouse and Azure Data Factory.

    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.