We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Hadoop is extensible — it's elastic."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"The most valuable feature is the database."
"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 performance is pretty good."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"It's good for storing historical data and handling analytics on a huge amount of data."
"Its integrability with the rest of the activities on Azure is most valuable."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"Powerful but easy-to-use and intuitive."
"The best part of this product is the extraction, transformation, and load."
"The most valuable feature is the copy activity."
"The solution can scale very easily."
"It is easy to deploy workflows and schedule jobs."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"Hadoop's security could be better."
"It would be good to have more advanced analytics tools."
"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 could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"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."
"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."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"Real-time replication is required, and this is not a simple task."
"We have experienced some issues with the integration. This is an area that needs improvement."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"The speed and performance need to be improved."
"The number of standard adaptors could be extended further."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"It's not particularly expensive."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"Understanding the pricing model for Data Factory is quite complex."
"This is a cost-effective solution."
"I would not say that this product is overly expensive."
"The licensing cost is included in the Synapse."
"The price you pay is determined by how much you use it."
Create, schedule, and manage your data integration at scale with Azure Data Factory - a hybrid data integration (ETL) service. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security.
Apache Hadoop is ranked 6th in Data Warehouse with 7 reviews while Azure Data Factory is ranked 2nd in Data Integration Tools with 25 reviews. Apache Hadoop is rated 7.6, while Azure Data Factory is rated 7.8. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". On the other hand, the top reviewer of Azure Data Factory writes "Easy to bring in outside capabilities, flexible, and works well". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Snowflake, VMware Tanzu Greenplum, Oracle Exadata and Microsoft Parallel Data Warehouse, whereas Azure Data Factory is most compared with Informatica PowerCenter, Talend Open Studio, Informatica Cloud Data Integration, Palantir Foundry and Denodo.
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.