Amazon EMR vs Snowflake: What are the differences?
Amazon EMR: Distribute your data and processing across a Amazon EC2 instances using Hadoop. Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year; Snowflake: The data warehouse built for the cloud. Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
Amazon EMR and Snowflake belong to "Big Data as a Service" category of the tech stack.
According to the StackShare community, Amazon EMR has a broader approval, being mentioned in 95 company stacks & 18 developers stacks; compared to Snowflake, which is listed in 29 company stacks and 11 developer stacks.
What is Amazon EMR?
What is Snowflake?
Need advice about which tool to choose?Ask the StackShare community!
Why do developers choose Snowflake?
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Amazon EMR?
What are the cons of using Snowflake?
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.
What's nice too is that it has SQL-based ML tools, and it has great GIS support!