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.
"It's good for storing historical data and handling analytics on a huge amount of data."
"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."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."
"The most valuable feature is the database."
"The performance is pretty good."
"The best thing about this solution is that it is very powerful and very cheap."
"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."
"The product is very user friendly."
"The most valuable feature of the solution is the analytics and that it can connect with Power BI."
"The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS."
"The most valuable feature of Microsoft Azure Synapse Analytics is the pipeline that is the ETL tool. It's very well designed and is overall very good. We usually don't use the ETL tool in Databricks, but we use the ETL tool in this solution."
"Overall deployment and integration is pretty fast."
"The most valuable feature is the level of processing power, and being able to complete tasks in parallel."
"Its scalability and ease of use are valuable. It is fairly simple for a tool that's that powerful. If you have a background in Microsoft SQL Server, it is a very easy-to-transition path."
"It's user-friendly and has a good dashboard."
"It could be more user-friendly."
"Hadoop's security could be better."
"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."
"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 integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"The upgrade path should be improved because it is not as easy as it should be."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"Microsoft Azure Synapse Analytics could improve the section in the solution where you can implement the Python Spark pipelines, it's not the same as in Databricks which would be better."
"Integration with other vendors has limitations and could be improved."
"The performance needs to improve in future releases."
"It needs strong support for social media, internet data, and native support for NoSQL."
"It could be more stable."
"Microsoft Azure Synapse Analytics can improve by increasing the size of the files that we can load on the platform. We have some files that are too large to be loaded and it would be a benefit to us if the limit was increased. Additionally, the way we use the tool for generating reports can be made better. They should add some drag-and-drop rules without the need of programming these rules using some programming language. It would be helpful if we did not need someone that was technically advanced to be able to do it with, such as someone with no IT background. Having a reporting tool without code would be great."
"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."
"Synapse Analytics needs to develop an automation framework because now you have to build a cache yourself. You have to build a pipeline in WhereScape, which does end-to-end pipeline automation well. Microsoft should come up with a framework to save people time. If they developed a tool like WhereScape, it would dramatically reduce development time."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 85 reviews. Apache Hadoop is rated 7.8, while Microsoft Azure Synapse Analytics is rated 7.8. 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 Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". Apache Hadoop is most compared with Azure Data Factory, Oracle Exadata, Snowflake, Teradata and BigQuery, whereas Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Snowflake, Oracle Autonomous Data Warehouse and AWS Lake Formation. See our Apache Hadoop vs. Microsoft Azure Synapse Analytics 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.