Apache Spark vs. Snowflake

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark
Score 8.9 out of 10
N/A
N/AN/A
Snowflake
Score 8.8 out of 10
N/A
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.N/A
Pricing
Apache SparkSnowflake
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SparkSnowflake
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache SparkSnowflake
Considered Both Products
Apache Spark
Chose Apache Spark
Databricks uses Spark as a foundation, and is also a great platform. It does bring several add-ons, which we did not feel needed by the time we evaluated - and haven't needed since then. One interesting plus in our opinion was the engineering support, which is great depending …
Snowflake

No answer on this topic

Top Pros
Top Cons
Best Alternatives
Apache SparkSnowflake
Small Businesses

No answers on this topic

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Score 8.7 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Google BigQuery
Google BigQuery
Score 8.7 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.7 out of 10
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Teradata Vantage
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SparkSnowflake
Likelihood to Recommend
9.3
(24 ratings)
8.9
(43 ratings)
Likelihood to Renew
10.0
(1 ratings)
10.0
(2 ratings)
Usability
8.7
(4 ratings)
9.3
(19 ratings)
Support Rating
8.7
(4 ratings)
9.9
(8 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Apache SparkSnowflake
Likelihood to Recommend
Apache
Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
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Snowflake Computing
Snowflake is well suited when you have to store your data and you want easy scalability and increase or decrease the storage per your requirement. You can also control the computing cost, and if your computing cost is less than or equal to 10% of your storage cost, then you don't have to pay for computing, which makes it cost-effective as well.
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Pros
Apache
  • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
  • Faster in execution times compare to Hadoop and PIG Latin
  • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
  • Interoperability between SQL and Scala / Python style of munging data
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Snowflake Computing
  • Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
  • Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
  • Snowflake manages concurrency better in our trials than other premium competitors
  • Snowflake has little to no setup and ramp up time
  • Snowflake offers online training for various employee types
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Cons
Apache
  • Memory management. Very weak on that.
  • PySpark not as robust as scala with spark.
  • spark master HA is needed. Not as HA as it should be.
  • Locality should not be a necessity, but does help improvement. But would prefer no locality
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Snowflake Computing
  • Add constraints for views and not just for tables
  • Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
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Likelihood to Renew
Apache
Capacity of computing data in cluster and fast speed.
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Snowflake Computing
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
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Usability
Apache
If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used
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Snowflake Computing
Because the fact that you can query tons of data in a few seconds is incredible, it also gives you a lot of functions to format and transform data right in your query, which is ideal when building data models in BI tools like Power BI, it is available as a connector in the most used BI tools worldwide.
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Support Rating
Apache
1. It integrates very well with scala or python. 2. It's very easy to understand SQL interoperability. 3. Apache is way faster than the other competitive technologies. 4. The support from the Apache community is very huge for Spark. 5. Execution times are faster as compared to others. 6. There are a large number of forums available for Apache Spark. 7. The code availability for Apache Spark is simpler and easy to gain access to. 8. Many organizations use Apache Spark, so many solutions are available for existing applications.
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Snowflake Computing
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
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Alternatives Considered
Apache
Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.
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Snowflake Computing
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
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Return on Investment
Apache
  • Business leaders are able to take data driven decisions
  • Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
  • Business is able come up with new product ideas
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Snowflake Computing
  • With separate compute and storage feature, the queries get executed quickly and it improves our overall productivity.
  • Earlier we were using a different product for analytical purposes, but with Snowflake's in-built analytical feature we are now able to save money.
  • Snowflake is cost efficient, features like auto suspend for compute resources helped to control the costs.
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ScreenShots

Snowflake Screenshots

Screenshot of Snowflake Installation