Apache Hadoop vs VMware Tanzu Greenplum comparison

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2,630 views|2,223 comparisons
89% willing to recommend
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2,089 views|1,712 comparisons
81% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Hadoop and VMware Tanzu Greenplum 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. VMware Tanzu Greenplum Report (Updated: March 2024).
768,740 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
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability.""Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform.""What comes with the standard setup is what we mostly use, but Ambari is the most important.""We selected Apache Hadoop because it is not dependent on third-party vendors.""The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics.""Hadoop File System is compatible with almost all the query engines.""It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database.""The most valuable feature is scalability and the possibility to work with major information and open source capability."

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"It's super easy to deploy and it also supports different languages and analytics.""We chose Greenplum because of the architecture in terms of clustering databases and being able to have, or at least utilize the resources that are sitting on a database.""The most valuable feature for us is horizontal scaling.""A very good, open-source platform.""With VMware Tanzu Greenplum, one can make a huge database table and analyze the queries by adding in the SQL command. Some hint or command for the query goes over the multi-parallel execution.""Scalable (Massive) Parallel Processing (MPP) – The ability to bring to bear large amounts of compute against large data sets with Greenplum and the EMC DCA has proven itself to be very effective.""Very fast for query processing.""The loading speed is very good."

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Cons
"It could be more user-friendly.""The integration with Apache Hadoop with lots of different techniques within your business can be a challenge.""It would be good to have more advanced analytics tools.""Hadoop's security could be better.""In certain cases, the configurations for dealing with data skewness do not make any sense.""The solution is very expensive.""Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them.""The upgrade path should be improved because it is not as easy as it should be."

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"Maintenance is time-consuming.""They need to enhance integration with other Big Data products... to integrate with Big Data platforms, and to open a bi-directional connection between Greenplum and Big Data.""If you have a user consuming a huge load of resources, it takes down the entire system.""They should add more analytics. Their documentation could also be improved so that I don't have to bother my co-workers and tech support so often.""Lacks sufficient inbuilt machine-learning functions for complex use cases.""they need to interact more with customers. They need to explain the features, especially when there are new releases of Greenplum. I know just from information I've found that it has other features, it can be used to for analytics, for integration with Big Data, Hadoop. They need to focus on this part with the customer.""Tanzu Greenplum's compression for GPText could be made more efficient.""Initial setup is a little complex. It took around two weeks to deploy."

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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 →

  • "It is the best product with best fit for price/performance customer objectives."
  • "Pricing is good compared to other products. It's fine."
  • "We are using the open-source version of this solution."
  • "Tanzu Greenplum's pricing is really competitive and gives excellent value for money."
  • "It’s an open-source solution."
  • More VMware Tanzu Greenplum Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Tools like Apache Hadoop are knowledge-intensive in nature. Unlike other tools in the market currently, we cannot understand knowledge-intensive products straight away. To use Apache Hadoop, a person… more »
    Top Answer:It’s an open-source solution. There are no expenses for using it.
    Top Answer:Maintenance is time-consuming. It takes time to VACUUM and ANALYZE the tables to remove the fragmentations.
    Ranking
    5th
    out of 34 in Data Warehouse
    Views
    2,630
    Comparisons
    2,223
    Reviews
    11
    Average Words per Review
    532
    Rating
    8.0
    9th
    out of 34 in Data Warehouse
    Views
    2,089
    Comparisons
    1,712
    Reviews
    6
    Average Words per Review
    370
    Rating
    7.3
    Comparisons
    Also Known As
    Greenplum, Pivotal Greenplum
    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.

    VMware Tanzu Greenplum is a massively parallel processing (MPP) data platform that enables organizations to store, manage, and analyze large volumes of data. It provides a unified analytics platform that supports various data types and sources, including structured, semi-structured, and unstructured data. 

    The solution is highly scalable and can be deployed on-premises, in the cloud, or hybrid environments. It includes advanced security features, high availability, and disaster recovery capabilities to minimize downtime and ensure business continuity. Tanzu Greenplum provides a comprehensive set of tools and services for building, deploying, and managing modern applications.

    Sample Customers
    Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
    General Electric, Conversant, China CITIC Bank, Aridhia, Purdue University
    Top Industries
    REVIEWERS
    Financial Services Firm38%
    Comms Service Provider25%
    Hospitality Company6%
    Consumer Goods Company6%
    VISITORS READING REVIEWS
    Financial Services Firm27%
    Computer Software Company10%
    Comms Service Provider6%
    University6%
    REVIEWERS
    Financial Services Firm52%
    Marketing Services Firm12%
    Comms Service Provider12%
    Retailer8%
    VISITORS READING REVIEWS
    Financial Services Firm30%
    Computer Software Company13%
    Manufacturing Company6%
    Insurance Company5%
    Company Size
    REVIEWERS
    Small Business34%
    Midsize Enterprise23%
    Large Enterprise43%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise75%
    REVIEWERS
    Small Business20%
    Midsize Enterprise14%
    Large Enterprise66%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    Buyer's Guide
    Apache Hadoop vs. VMware Tanzu Greenplum
    March 2024
    Find out what your peers are saying about Apache Hadoop vs. VMware Tanzu Greenplum and other solutions. Updated: March 2024.
    768,740 professionals have used our research since 2012.

    Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while VMware Tanzu Greenplum is ranked 9th in Data Warehouse with 36 reviews. Apache Hadoop is rated 7.8, while VMware Tanzu Greenplum is rated 7.8. The top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". On the other hand, the top reviewer of VMware Tanzu Greenplum writes "Very efficient at large scale analytics; lacks inbuilt machine-learning functions for complex use cases". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Amazon Redshift, whereas VMware Tanzu Greenplum is most compared with Oracle Exadata, Vertica, Oracle Database Appliance, Snowflake and Teradata. See our Apache Hadoop vs. VMware Tanzu Greenplum 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.