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 scalability of Apache Hadoop is very good."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"The most valuable feature is the database."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"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 File System is compatible with almost all the query engines."
"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"The adaptation to development languages is most valuable. Our developers can SQL code or something else. It has been convenient in that regard."
"The feature that is really striking is the ability to translate the SQL workloads into the NoSQL version that can be used by Snowflake."
"It is a very well-distributed system. It has different data engines for different applications. Many applications can use different computational engines at the same time. In terms of data processing, the feeling was similar to working with a relational database but in a scalable way."
"The querying speed is fast."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services."
"The solution is easy to use."
"I have found the solution's most valuable features to be storage, flexibility, ease of use, and security."
"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."
"Hadoop's security could be better."
"It could be more user-friendly."
"It needs better user interface (UI) functionalities."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"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."
"It would be good to have more advanced analytics tools."
"The stability of the solution needs improvement."
"These days, they are pushing users towards the GUI or graphical version. However, I am more familiar with the classic version. I'd like to continue to work with it using the older approach."
"The user interface continues to be an issue, especially when we need to get data out of Snowflake. It's very easy to get data in, but it's not too easy to get it out or extract it."
"Snowflake has support for stored procedures, but it is not that powerful."
"Its stability could be better."
"Availability is a problem."
"Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues."
"To ensure the proper functioning of Snowflake as an MDS, it relies heavily on other partner tools."
"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."
Apache Hadoop is ranked 6th in Data Warehouse with 34 reviews while Snowflake is ranked 1st in Data Warehouse with 94 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.