We performed a comparison between Apache Hadoop and Microsoft Azure Synapse Analytics based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Synapse has a slight edge in this comparison. According to its users, it is more user-friendly and less expensive than Hadoop.
"We selected Apache Hadoop because it is not dependent on third-party vendors."
"The scalability of Apache Hadoop is very good."
"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."
"What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies."
"The performance is pretty good."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"Hadoop is extensible — it's elastic."
"The architecture, including compute and storage, is good."
"Fills the gap between big data and classic data warehouses."
"The features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."
"One of the most valuable features of this solution is its ability to integrate well with other services offered by Azure."
"It's scalable; you can scale up and scale down."
"The product is very user friendly."
"I have not used the technical support from Microsoft Azure Synapse Analytics, but I worked with the developers at Microsoft who were top-notch."
"The most important feature for me is the integration with PolyBase."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"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."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"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."
"Hadoop's security could be better."
"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 is very expensive."
"It would be ideal if the solution could be better used intuitively by the staff without having a great deal of training."
"It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft."
"The initial setup is complex."
"We'd, of course, always like to pay less for the service if we can."
"Synapse Analytics is generally stable, but its performance can be slow when performing very large datasets."
"Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better."
"The only concern for us is the cost part. When it comes to the implementation and the support and maintenance, we see high-cost implications."
"If I'm looking for something good in the cloud, I would want it to have better standard connectors."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
Apache Hadoop is ranked 6th in Data Warehouse with 7 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 44 reviews. Apache Hadoop is rated 7.8, while Microsoft Azure Synapse Analytics is rated 7.8. 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 Microsoft Azure Synapse Analytics writes "Scalable, intuitive, facilitates compliance and keeping your data secure". Apache Hadoop is most compared with Snowflake, Oracle Exadata, VMware Tanzu Greenplum, Azure Data Factory and Teradata, whereas Microsoft Azure Synapse Analytics is most compared with Snowflake, Amazon Redshift, Azure Data Factory, SAP BW4HANA and Oracle Autonomous Data Warehouse.
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.
