Apache Hadoop vs IBM Db2 Warehouse comparison

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Executive Summary

We performed a comparison between Apache Hadoop and IBM Db2 Warehouse 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. IBM Db2 Warehouse Report (Updated: November 2022).
656,862 professionals have used our research since 2012.
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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:
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial.""The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable.""I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed.""One valuable feature is that we can download data.""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.""We selected Apache Hadoop because it is not dependent on third-party vendors.""Hadoop is extensible — it's elastic."

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"It can be mounted on the cloud, which is a huge plus. If the client, for example, starts small with on-premise deployment and then it rapidly needs to grow, we can transfer this to the cloud easily.""Some of the best features are stored procedures, parallelism, and different indexing strategies.""The analytics engine is not bad at forecasting predictions.""I think it scales really well and as long as you take enough time to learn a little bit about it, it works really well."

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"I think more of the solution needs to be focused around the panel processing and retrieval of data.""The integration with Apache Hadoop with lots of different techniques within your business can be a challenge.""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.""What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly.""It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it.""Real-time data processing is weak. This solution is very difficult to run and implement.""Hadoop's security could be better.""The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."

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"The biggest challenge anyone could have with Db2 Warehouse is their references or online resources and documentation. They are very, very, very limited on the web.""There should be more material available for training and training should be free.""The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting.""The biggest problems we have is when the backup solution is failing or slow and we run out of log space, which has happened probably a couple of times in the last four years."

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Pricing and Cost Advice
  • "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."
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  • "In a traditional on-prem database, in a data warehouse, the solution is probably on the expensive side."
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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:Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial.
    Top Answer:I am not sure about the price, but in terms of usability and utility of the software as a whole, I would rate it a three and a half to four out of five.
    Top Answer:Some of the best features are stored procedures, parallelism, and different indexing strategies.
    Top Answer:In a traditional on-prem database, in a data warehouse, the solution is probably on the expensive side.
    Top Answer:The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting.
    out of 32 in Data Warehouse
    Average Words per Review
    out of 32 in Data Warehouse
    Average Words per Review
    Also Known As
    InfoSphere Warehouse, IBM InfoSphere Warehouse
    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.
    InfoSphere Warehouse is a suite of products that combines the strength of DB2 with a data warehousing infrastructure from IBM. You can use InfoSphere Warehouse to build a complete data warehousing solution that includes a highly scalable relational database, data access capabilities, and front-end analysis tools.
    Learn more about Apache Hadoop
    Learn more about IBM Db2 Warehouse
    Sample Customers
    Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
    Alameda County Social Services Agency, Sui Southern Gas Company Limited
    Top Industries
    Financial Services Firm46%
    Comms Service Provider31%
    Hospitality Company8%
    Consumer Goods Company8%
    Financial Services Firm19%
    Computer Software Company18%
    Comms Service Provider10%
    Manufacturing Company6%
    Computer Software Company17%
    Financial Services Firm17%
    Comms Service Provider11%
    Insurance Company8%
    Company Size
    Small Business32%
    Midsize Enterprise29%
    Large Enterprise39%
    Small Business16%
    Midsize Enterprise12%
    Large Enterprise72%
    Small Business19%
    Midsize Enterprise11%
    Large Enterprise70%
    Buyer's Guide
    Apache Hadoop vs. IBM Db2 Warehouse
    November 2022
    Find out what your peers are saying about Apache Hadoop vs. IBM Db2 Warehouse and other solutions. Updated: November 2022.
    656,862 professionals have used our research since 2012.

    Apache Hadoop is ranked 6th in Data Warehouse with 9 reviews while IBM Db2 Warehouse is ranked 13th in Data Warehouse with 4 reviews. Apache Hadoop is rated 8.0, while IBM Db2 Warehouse is rated 7.4. The top reviewer of Apache Hadoop writes "Has good processing power and speed and is capable of handling large volumes of data and doing online analysis". On the other hand, the top reviewer of IBM Db2 Warehouse writes "If you have good people designing how the data is stored, this is a marvelous tool". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Snowflake, Azure Data Factory, Oracle Exadata and Teradata, whereas IBM Db2 Warehouse is most compared with Oracle Exadata, Amazon Redshift, Snowflake, Microsoft Azure Synapse Analytics and BigQuery. See our Apache Hadoop vs. IBM Db2 Warehouse report.

    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.