Apache Hadoop vs Microsoft Analytics Platform System comparison

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Apache Logo
2,467 views|2,109 comparisons
87% willing to recommend
Microsoft Logo
309 views|228 comparisons
66% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Hadoop and Microsoft Analytics Platform System based on real PeerSpot user reviews.

Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Apache Hadoop vs. Microsoft Analytics Platform System Report (Updated: May 2024).
771,170 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The scalability of Apache Hadoop is very good.""The best thing about this solution is that it is very powerful and very cheap.""Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done.""As compared to Hive on MapReduce, Impala on MPP returns results of SQL queries in a fairly short amount of time, and is relatively fast when reading data into other platforms like R.""Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability.""High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization.""I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed.""The most valuable features are powerful tools for ingestion, as data is in multiple systems."

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"We leverage its capabilities for many applications. We can integrate with our databases, like Oracle, MySQL, or any other, using Microsoft Integration Services.""Microsoft Analytics Platform System's most valuable feature is its ecosystems and seamless integration with other Microsoft reporting platforms and databases.""I like that it's integrated with other Azure products.""Helps our customers to discover trends, which provides useful information based on their business.""The Cube Solution is quite different when compared to the rest of the competition and has unique functionality for advanced analytics.""This is a well-integrated solution and that integration empowers results.""It is closely integrated with other products in the MS portfolio.""This solution will connect to any database, you can combine databases, and you can create a cube or tabular model."

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Cons
"Since it is an open-source product, there won't be much support.""I think more of the solution needs to be focused around the panel processing and retrieval of data.""Real-time data processing is weak. This solution is very difficult to run and implement.""It needs better user interface (UI) functionalities.""It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake.""It could be more user-friendly.""In certain cases, the configurations for dealing with data skewness do not make any sense.""In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."

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"Microsoft Analytics Platform System could have better support.""We need better real-time analytics capabilities. It's a bit challenging for us.""Functionality needs to be more up-to-date with competing products.""The pricing model needs to be improved.""I think the biggest problem with the product is that it does a data ingest model, which is very expensive.""​Hybrid environments are complex to manage.""Machine learning and artificial intelligence capabilities need to be more friendly for beginning users.""The flexibility of this solution needs to be improved because you cannot make changes at every one of the different steps."

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Pricing and Cost Advice
  • "Do take into consider that data storage and compute capacity scale differently and hence purchasing a "boxed" / 'all-in-one" solution (software and hardware) might not be the best idea."
  • "​There are no licensing costs involved, hence money is saved on the software infrastructure​."
  • "This is a low cost and powerful solution."
  • "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."
  • "The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
  • "We just use the free version."
  • More Apache Hadoop Pricing and Cost Advice →

  • "The initial price is lower than Oracle, but extensive use of SQL may lead to a higher total cost of ownership."
  • "Users have to pay extra for premium-level technical support."
  • "We are currently paying $200,000 a year for all the different parts of the suite during an ingest model Microsoft now charges us $700,000 a year."
  • "I rate Microsoft Analytics Platform System a seven out of ten for pricing."
  • More Microsoft Analytics Platform System Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: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.
    Top Answer:Since it is an open-source product, there won't be much support. So, you have to have deeper knowledge. You need to improvise based on that.
    Top Answer:We leverage its capabilities for many applications. We can integrate with our databases, like Oracle, MySQL, or any other, using Microsoft Integration Services.
    Top Answer:It's not too confusing. It's based on features, and we don't have to buy additional licenses.
    Top Answer:We need better real-time analytics capabilities. It's a bit challenging for us. Moreover, there are some permission limitations.
    Ranking
    5th
    out of 35 in Data Warehouse
    Views
    2,467
    Comparisons
    2,109
    Reviews
    11
    Average Words per Review
    573
    Rating
    7.9
    17th
    out of 35 in Data Warehouse
    Views
    309
    Comparisons
    228
    Reviews
    2
    Average Words per Review
    439
    Rating
    7.5
    Comparisons
    Also Known As
    Microsoft APS, MS Analytics Platform System
    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.
    The Microsoft Analytics Platform System can meet the demands of your evolving data warehouse environment with its scale-out, massively parallel processing integrated system supporting hybrid data warehouse scenarios. It provides the ability to query across relational and non-relational data by leveraging Microsoft PolyBase and industry-leading big data technologies. It offers the lowest price per terabyte for large data warehouse workloads.
    Sample Customers
    Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
    Transport for London, E-Plus Mobilfunk GmbH & Co. KG, Prometeia, Tangerine, SSM Health Care, Service Corporation International
    Top Industries
    REVIEWERS
    Financial Services Firm38%
    Comms Service Provider25%
    Hospitality Company6%
    Consumer Goods Company6%
    VISITORS READING REVIEWS
    Financial Services Firm28%
    Computer Software Company10%
    University6%
    Comms Service Provider6%
    VISITORS READING REVIEWS
    Financial Services Firm13%
    Computer Software Company13%
    University11%
    Energy/Utilities Company8%
    Company Size
    REVIEWERS
    Small Business34%
    Midsize Enterprise20%
    Large Enterprise46%
    VISITORS READING REVIEWS
    Small Business14%
    Midsize Enterprise11%
    Large Enterprise74%
    REVIEWERS
    Small Business36%
    Large Enterprise64%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise6%
    Large Enterprise74%
    Buyer's Guide
    Apache Hadoop vs. Microsoft Analytics Platform System
    May 2024
    Find out what your peers are saying about Apache Hadoop vs. Microsoft Analytics Platform System and other solutions. Updated: May 2024.
    771,170 professionals have used our research since 2012.

    Apache Hadoop is ranked 5th in Data Warehouse with 33 reviews while Microsoft Analytics Platform System is ranked 17th in Data Warehouse with 9 reviews. Apache Hadoop is rated 7.8, while Microsoft Analytics Platform System is rated 6.6. The top reviewer of Apache Hadoop writes "Handles huge data volumes and create your own workflows and tables but you need to have deeper knowledge". On the other hand, the top reviewer of Microsoft Analytics Platform System writes "Offers smooth data integration between systems, but requires better real-time analytics capabilities". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Microsoft Analytics Platform System is most compared with Microsoft Azure Synapse Analytics, Teradata, IBM Netezza Performance Server and Snowflake. See our Apache Hadoop vs. Microsoft Analytics Platform System report.

    See our list of best Data Warehouse vendors.

    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.