Compare Apache Hadoop vs. Snowflake

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Apache Hadoop Logo
12,184 views|10,135 comparisons
Snowflake Logo
30,694 views|20,985 comparisons
Most Helpful Review
Find out what your peers are saying about Apache Hadoop vs. Snowflake and other solutions. Updated: January 2021.
454,950 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"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.""The best thing about this solution is that it is very powerful and very cheap.""What comes with the standard setup is what we mostly use, but Ambari is the most important.""The ability to add multiple nodes without any restriction is the solution's most valuable aspect.""It's good for storing historical data and handling analytics on a huge amount of data.""The most valuable feature is the database.""The most valuable features are powerful tools for ingestion, as data is in multiple systems.""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."

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"As long as you don't need to worry about the storage or cost, this solution would be one of the best ones on the market for scalability purposes.""The most valuable features are the clustering, LS50, being able to change the size, the pay per use feature, the flexibility with many different sources and analytic applications.""They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises.""The initial setup is straightforward. You just need to follow the documentation.""The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.""It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL.""I like the idea that you can assign roles and responsibilities, limiting access to data.""The most valuable feature is the snapshot database. In one second, you can just take a snapshot of the database for test purposes."

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Cons
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it.""The upgrade path should be improved because it is not as easy as it should be.""In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency.""There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution.""The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment.""It would be good to have more advanced analytics tools.""It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake.""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."

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"There are some stored procedures that we've had trouble with. The solution also needs to fine-tune the connectors to be able to connect into the system source.""Support needs improvement, as it can take several days before you get some initial support.""The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template.""The solution could improve the user interface and add functionality to the system.""Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway.""They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in.""If you go with one cloud provider, you can't switch.""Availability is a problem."

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Pricing and Cost Advice
"This is a low cost and powerful solution."

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"Pricing can be confusing for customers.""The whole licensing system is based on credit points. You can also make a license agreement with the company so that you buy credit points and then you use them. What you do not use in one year can be carried over to the next year.""You pay based on the data that you are storing in the data warehouse and there are no maintenance costs.""It is not cheap.""The pricing for Snowflake is competitive.""On average, with the number of queries that we run, we pay approximately $200 USD per month.""Pricing is approximately $US 50 per DB. Terabyte is around $US 50 per month.""The price of Snowflake is very reasonable."

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Answers from the Community
Miriam Tover
author avatarManish-Kapoor (Tata Consultancy Services)
Consultant

Interactive querying as a consumption pattern is something Snowflake handles much better than Hadoop and related query engine options - Impala, Presto, Drill etc. Heavy data scientists query workload can be an expensive query pattern on Snowflake and Hadoop can provide a more cost-efficient solution. Hadoop is also still relevant as a back-end data processing engine, instead of leveraging Snowflake for data transformation due to higher cost as well as limited procedural language capabilities (javascript based stored procedures). Snowflake fares much better than Hadoop in terms of administrative complexity.

author avatarSreenivasan Ramanujam
User

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.

Questions from the Community
Top Answer: 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… more »
Top Answer: SQreamDB is a GPU DB. It is not suitable for real-time oltp of course. Cassandra is best suited for OLTP database use cases, when you need a scalable database (instead of SQL server, Postgres)… more »
Top Answer: The most valuable features are powerful tools for ingestion, as data is in multiple systems.
Top Answer: The most valuable feature is the snapshot database. In one second, you can just take a snapshot of the database for test purposes.
Top Answer: The primary use case is big data warehouses.
Ranking
3rd
out of 30 in Data Warehouse
Views
12,184
Comparisons
10,135
Reviews
10
Average Words per Review
426
Rating
7.7
1st
out of 30 in Data Warehouse
Views
30,694
Comparisons
20,985
Reviews
21
Average Words per Review
531
Rating
8.2
Popular Comparisons
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Compared 7% of the time.
Compared 7% of the time.
Compared 6% of the time.
Compared 5% of the time.
Also Known As
Snowflake Computing
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Apache
Snowflake Computing
Overview
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Snowflake provides a data warehouse built for the cloud, delivering a solution capable of solving problems for which legacy, on-premises and cloud data platforms were not designed.

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Sample Customers
Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web LabAccordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Top Industries
VISITORS READING REVIEWS
Computer Software Company34%
Comms Service Provider17%
Financial Services Firm13%
Media Company6%
REVIEWERS
Computer Software Company33%
Manufacturing Company22%
Media Company11%
Healthcare Company11%
VISITORS READING REVIEWS
Computer Software Company34%
Comms Service Provider15%
Financial Services Firm6%
Media Company5%
Company Size
REVIEWERS
Small Business37%
Midsize Enterprise21%
Large Enterprise42%
REVIEWERS
Small Business28%
Midsize Enterprise16%
Large Enterprise56%
VISITORS READING REVIEWS
Small Business3%
Midsize Enterprise19%
Large Enterprise78%
Find out what your peers are saying about Apache Hadoop vs. Snowflake and other solutions. Updated: January 2021.
454,950 professionals have used our research since 2012.

Apache Hadoop is ranked 3rd in Data Warehouse with 10 reviews while Snowflake is ranked 1st in Data Warehouse with 21 reviews. Apache Hadoop is rated 7.8, while Snowflake is rated 8.2. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". On the other hand, the top reviewer of Snowflake writes "Fast, convenient and requires almost no administration". Apache Hadoop is most compared with VMware Tanzu Greenplum, Oracle Exadata, Vertica, Teradata and Microsoft Azure Synapse Analytics, whereas Snowflake is most compared with Microsoft Azure Synapse Analytics, Amazon Redshift, Firebolt, Vertica and Oracle Exadata. See our Apache Hadoop vs. Snowflake report.

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