Snowflake vs Stitch: What are the differences?
What is 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.
What is Stitch? All your data. In your data warehouse. In minutes. Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.
Snowflake and Stitch can be categorized as "Big Data as a Service" tools.
Instacart, HousingAnywhere, and Auto Trader are some of the popular companies that use Snowflake, whereas Stitch is used by HousingAnywhere, Kalibrr, and Firecracker. Snowflake has a broader approval, being mentioned in 29 company stacks & 11 developers stacks; compared to Stitch, which is listed in 22 company stacks and 4 developer stacks.
What is Snowflake?
What is Stitch?
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Why do developers choose Snowflake?
What are the cons of using Snowflake?
What are the cons of using Stitch?
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Looker , Stitch , Amazon Redshift , dbt
We recently moved our Data Analytics and Business Intelligence tooling to Looker . It's already helping us create a solid process for reusable SQL-based data modeling, with consistent definitions across the entire organizations. Looker allows us to collaboratively build these version-controlled models and push the limits of what we've traditionally been able to accomplish with analytics with a lean team.
For Data Engineering, we're in the process of moving from maintaining our own ETL pipelines on AWS to a managed ELT system on Stitch. We're also evaluating the command line tool, dbt to manage data transformations. Our hope is that Stitch + dbt will streamline the ELT bit, allowing us to focus our energies on analyzing data, rather than managing it.
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!