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."Data ingestion: It has rapid speed, if Apache Accumulo is used."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"Hadoop is extensible — it's elastic."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"Provides good security and reliability."
"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."
"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 standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."
"The analytics engine is not bad at forecasting predictions."
"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."
"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."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"I would like to see more direct integration of visualization applications."
"Hadoop's security could be better."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"The upgrade path should be improved because it is not as easy as it should be."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"In terms of improvement, IBM Db2 Warehouse should be more scalable."
"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."
"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 challenge anyone could have with Db2 Warehouse is their references or online resources and documentation. They are very, very, very limited on the web."
"Lacks sufficient documentation and particularly in Spanish."
"IBM Db2 Warehouse needs to improve its interface."
Apache Hadoop is ranked 5th in Data Warehouse with 33 reviews while IBM Db2 Warehouse is ranked 13th in Data Warehouse with 8 reviews. Apache Hadoop is rated 7.8, while IBM Db2 Warehouse is rated 7.6. 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 IBM Db2 Warehouse writes "Useful for ETL process and has good documentation ". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Oracle Autonomous Data Warehouse, whereas IBM Db2 Warehouse is most compared with Oracle Exadata, Snowflake, Amazon Redshift, Teradata and IBM Db2 Warehouse on Cloud. See our Apache Hadoop vs. IBM Db2 Warehouse report.
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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.
