We performed a comparison between Apache Hadoop and Snowflake 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."The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"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 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."
"Apache Hadoop is crucial in projects that save and retrieve data daily. Its valuable features are scalability and stability. It is easy to integrate with the existing infrastructure."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"The scalability of Apache Hadoop is very good."
"The performance is pretty good."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"Time travel is one feature that really helps us out."
"This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere."
"It is a highly scalable solution. There is no limit on storage or computing."
"Once you have finished your designs they can be easily imported to Snowflake and the information can be readily accessed without an IT expert."
"The most valuable feature has been the Snowflake data sharing and dynamic data masking."
"This solution has helped our organization by being easy to maintain and having good technical support."
"The ETL and data ingestion capabilities are better in this solution as compared to SQL Server. SQL Server doesn't do much data ingestion, but Snowflake can do it quite conveniently."
"It helped us to build MVP (minimum viable product) for our idea of building a data warehouse model for small businesses."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"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."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The solution is very expensive."
"I would like to see more direct integration of visualization applications."
"Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them."
"To ensure the proper functioning of Snowflake as an MDS, it relies heavily on other partner tools."
"I can only access Snowflake from the web. It would be better if we could have an app that we can install locally on our laptops to connect to the server without needing to go to the web page. Apart from that, it's hard to point out any limitations in the tool."
"Snowflake could improve migration. It should be made easier. It would be beneficial if it could offer some OLTP features. One of our customers was using Oracle for both data warehousing and OLTP workloads, and they were able to migrate their data warehousing workloads to Snowflake without major issues. However, for some of their OLTP requirements, such as needing a response time of fewer than 10 milliseconds for certain queries, Snowflake is currently unable to provide that."
"Snowflake has support for stored procedures, but it is not that powerful."
"It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud."
"It's difficult to know how to size everything correctly."
"The cost efficiency and monitoring of this solution could be improved. It's easy to spend a lot on Snowflake and it does offer monitoring tools but they're pretty basic."
"I am still in the learning stage. It has good security, but it can always be more secure."
Apache Hadoop is ranked 6th in Data Warehouse with 34 reviews while Snowflake is ranked 1st in Data Warehouse with 95 reviews. Apache Hadoop is rated 7.8, while Snowflake is rated 8.4. 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 Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Teradata and BigQuery, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Teradata Cloud Data Warehouse. See our Apache Hadoop vs. Snowflake report.
See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.
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Apache Hadoop is for data lake use cases. But getting data out of Hadoop for meaningful analytics is indeed need quite an amount of work. by either using spark/Hive/presto and so on. The way i look at Snowflake and Hadoop is they complement each other. For data lake you can use hadoop and then for datawarehouse companies can use snowflake. Depending on the size of the company you can turn snowflake into a data lake use case too. Snowflake is SQL friendly and you don't need to carry out any circus to get the data in and out of snowflake.