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Apache Hadoop vs Microsoft Azure Synapse Analytics comparison

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Find out what your peers are saying about Snowflake Computing, Oracle, Micro Focus and others in Data Warehouse. Updated: January 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
"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 most valuable features are powerful tools for ingestion, as data is in multiple systems.""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."

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"We have found that it is easy to develop and to do the analytics in the modules of data.""Technical support is okay in terms of the help they provide.""Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across.""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 stability is pretty good.""The most valuable feature is performance gains.""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.""We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for difference sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on."

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Cons
"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.""Hadoop's security could be better.""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.""The solution is very expensive."

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"The need to improve a little bit in terms of user-friendliness.""Indicating what areas need improvement in this solution is a difficult question because the organizations that I am working for are really new in this area. However, an even better more simple interface, or perhaps an extension of a connector app store solution, would be helpful.""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.""Comes with a pretty steep learning curve.""The product could be more feature-rich.""Could have more connectors and better integration for Hadoop.""This solution needs to have query caching so that if the same query is run and the results are available, it will return the data from the cache without having to re-run the query."

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Pricing and Cost Advice
Information Not Available
  • "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."
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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: 
    Hadoop is extensible — it's elastic.
    Top Answer: 
    Hadoop's security could be better.
    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 »
    Top Answer: 
    Fills the gap between big data and classic data warehouses.
    Ranking
    7th
    out of 30 in Data Warehouse
    Views
    7,075
    Comparisons
    5,891
    Reviews
    5
    Average Words per Review
    436
    Rating
    7.6
    2nd
    Views
    26,962
    Comparisons
    19,760
    Reviews
    31
    Average Words per Review
    530
    Rating
    8.0
    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.

    Azure SQL Data Warehouse is a Fast, flexible, and secure analytics platform for the enterprise. Azure SQL Data Warehouse lets you independently scale compute and storage, while pausing and resuming your data warehouse within minutes through a massively parallel processing architecture designed for the cloud. Seamlessly create your hub for analytics along with native connectivity with data integration and visualization services, all while using your existing SQL and BI skills.

    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 Firm43%
    Comms Service Provider29%
    Consumer Goods Company14%
    Government14%
    VISITORS READING REVIEWS
    Computer Software Company28%
    Comms Service Provider18%
    Financial Services Firm13%
    Energy/Utilities Company5%
    REVIEWERS
    Computer Software Company21%
    Comms Service Provider16%
    Manufacturing Company11%
    Insurance Company11%
    VISITORS READING REVIEWS
    Computer Software Company27%
    Comms Service Provider18%
    Financial Services Firm6%
    Energy/Utilities Company6%
    Company Size
    REVIEWERS
    Small Business38%
    Midsize Enterprise24%
    Large Enterprise38%
    REVIEWERS
    Small Business33%
    Midsize Enterprise21%
    Large Enterprise46%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise13%
    Large Enterprise71%
    Find out what your peers are saying about Snowflake Computing, Oracle, Micro Focus and others in Data Warehouse. Updated: January 2022.
    563,148 professionals have used our research since 2012.

    Apache Hadoop is ranked 7th in Data Warehouse with 5 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 33 reviews. Apache Hadoop is rated 7.6, while Microsoft Azure Synapse Analytics 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 Azure Synapse Analytics writes "Scalable, intuitive, facilitates compliance and keeping your data secure". Apache Hadoop is most compared with Snowflake, VMware Tanzu Greenplum, Oracle Exadata, Teradata and Vertica, whereas Microsoft Azure Synapse Analytics is most compared with Snowflake, Amazon Redshift, SAP BW4HANA, Oracle Autonomous Data Warehouse and AWS Lake Formation.

    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.