IT Central Station is now PeerSpot: Here's why

Apache Hadoop vs Microsoft Analytics Platform System comparison

You must select at least 2 products to compare!
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
"We selected Apache Hadoop because it is not dependent on third-party vendors.""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.""The scalability of Apache Hadoop is very 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.""The performance is pretty good."

More Apache Hadoop Pros →

"This is a well-integrated solution and that integration empowers results."

More Microsoft Analytics Platform System Pros →

"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.""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 integration with Apache Hadoop with lots of different techniques within your business can be a challenge.""The solution is very expensive.""Real-time data processing is weak. This solution is very difficult to run and implement.""Hadoop's security could be better."

More Apache Hadoop Cons →

"Releases of new products and functionality is never accompanied by associated documentation, training and resources that adequately explain the release."

More Microsoft Analytics Platform System Cons →

Pricing and Cost Advice
  • "The price of Apache Hadoop could be less expensive."
  • More Apache Hadoop Pricing and Cost Advice →

    Information Not Available
    Use our free recommendation engine to learn which Data Warehouse solutions are best for your needs.
    608,010 professionals have used our research since 2012.
    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.
    Ask a question

    Earn 20 points

    out of 30 in Data Warehouse
    Average Words per Review
    out of 30 in Data Warehouse
    Average Words per Review
    Also Known As
    Microsoft APS, MS Analytics Platform System
    Learn More
    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.
    Learn more about Apache Hadoop
    Learn more about Microsoft Analytics Platform System
    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
    Financial Services Firm50%
    Comms Service Provider25%
    Consumer Goods Company13%
    Computer Software Company26%
    Comms Service Provider15%
    Financial Services Firm15%
    Energy/Utilities Company5%
    Computer Software Company24%
    Comms Service Provider21%
    Financial Services Firm7%
    Insurance Company6%
    Company Size
    Small Business36%
    Midsize Enterprise27%
    Large Enterprise36%
    Small Business15%
    Midsize Enterprise14%
    Large Enterprise72%
    Small Business38%
    Large Enterprise63%
    Small Business19%
    Midsize Enterprise13%
    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 Analytics Platform System is ranked 10th in Data Warehouse with 1 review. Apache Hadoop is rated 7.6, while Microsoft Analytics Platform System is rated 8.0. 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 Analytics Platform System writes "This suite of products performs many different and important tasks as a well-integrated system". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Snowflake, Oracle Exadata, VMware Tanzu Greenplum and Yellowbrick Cloud Data Warehouse, whereas Microsoft Analytics Platform System is most compared with Microsoft Azure Synapse Analytics, Teradata, Amazon Redshift, IBM Netezza Performance Server and Snowflake.

    See our list of best Data Warehouse vendors and best Cloud 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.