We performed a comparison between Apache Hadoop and Azure Data Factory based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The tool's stability is good."
"Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done."
"Hadoop is extensible — it's elastic."
"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."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"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."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"The trigger scheduling options are decently robust."
"From what we have seen so far, the solution seems very stable."
"The solution can scale very easily."
"The most important feature is that it can help you do the multi-threading concepts."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"The most valuable feature of this solution would be ease of use."
"It needs better user interface (UI) functionalities."
"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."
"The load optimization capabilities of the product are an area of concern where improvements are required."
"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."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."
"General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error."
"There are limitations when processing more than one GD file."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"I have not found any real shortcomings within the product."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews. Apache Hadoop is rated 7.8, while Azure Data Factory is rated 8.0. 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 Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake, Teradata and BigQuery, whereas Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics. See our Apache Hadoop vs. Azure Data Factory report.
See our list of best Cloud Data Warehouse vendors.
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