We performed a comparison between Apache Hadoop and Snowflake Analytics 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."What comes with the standard setup is what we mostly use, but Ambari is the most important."
"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."
"It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"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."
"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."
"The scalability of Apache Hadoop is very good."
"The Snowflake features I find most beneficial for data analysis are primarily related to analytics, particularly their features like materialized views and queues, which are especially useful for dashboarding purposes."
"One of the valuable features is the solution’s time travel capability. The solution is highly stable. The solution is highly scalable. The initial setup is straightforward, and the deployment process is quick and efficient. I recommend the solution. Overall, I rate it a perfect ten."
"The platform not only provides ease of use but also stands out for its speedy execution, conveying a sense of robustness and reliability that I find appealing."
"Very good flexibility and it offers computation completely decoupled from the storage."
"Deployment is straightforward as it's a SaaS product. No maintenance required."
"The most valuable feature of Snowflake Analytics is its performance."
"Scaling is very high – there's no problem for scaling purposes. The learning curve is very small. And there are a lot of advanced features like handling duplicates, security, data governance, data sharing, and data cloning."
"The performance has been good."
"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."
"Hadoop's security could be better."
"It would be good to have more advanced analytics tools."
"The stability of the solution needs improvement."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"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."
"Snowflake should include a WHERE clause for building data pipelines."
"Moving data from legacy systems to Snowflake is not that easy. There are some cases where processors are not actually compatible with Snowflake."
"One area that could benefit from enhancement is the user interface for more visual ESM features."
"The technical support is not very good."
"Snowflake could improve in the areas of advanced machine learning AML and generative AI."
"Implementing everything on-premise is challenging because it require proper support from advisors, DBAs, and others."
"A room for improvement in Snowflake Analytics is Spark, particularly its connector for Spark. An additional feature I'd like to see in the next release of the solution is built-in analytics."
"The UI could be more user-friendly."
Apache Hadoop is ranked 5th in Data Warehouse with 33 reviews while Snowflake Analytics is ranked 6th in Cloud Data Warehouse with 30 reviews. Apache Hadoop is rated 7.8, while Snowflake Analytics 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 Analytics writes "A scalable tool useful for data lake and data mining processes". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Snowflake Analytics is most compared with Azure Data Factory, Adobe Analytics, Mixpanel, Amplitude and Glassbox. See our Apache Hadoop vs. Snowflake Analytics report.
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We monitor all Cloud 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.
