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Aws snowflake vs redshift9/13/2023 ![]() It check all objects in schema and then tries to restore all objects to AT time. Snowflake sees a lot of success in the retail vertical because of clients who don't want to run their workloads on AWS.Ĭreate schema xxx clone yy(at. Separation of compute and storage sizing (with the RA3 instances) was a huge addition to Redshift to compete with Snowflake and Big Query.įinally, Snowflake has the benefit of being able to be deployed on AWS, Azure, or GCP, even within a single Organization, meaning you can run it across multiple clouds if you wish to meet client needs. Redshift Serverless is designed to take the Snowflake approach (only pay for what you use) but it's still fairly new. Snowflake is charged per credit, so your costs scale with your utilisation, which can get expensive if you don't optimise your workload. If your cluster is lightly utilised, you're burning money. With Redshift, traditionally you're paying an hourly cost based on the size of the cluster and storage requirements. There's a premium for that reduced maintenance model. Things like the permission model in Redshift can be quite inflexible when compared to Snowflake, which has a very modern role-based permission model. Since Redshift is based on Paraccel, which in turn was based on PostgresSQL, there are some legacy implications in Redshift based on the very old Postgres version forked back in the day. Snowflake does the majority of that for you. Redshift has made improvements in this area the last few years, but you still need to get under the hood at times and dive into vacuums and distribution keys and compression schemes and the like. In Snowflake, everything is just there as part of the experience, no messing around with IAM etc.Īnother area of difference is around maintenance. It's a common theme across AWS products to see new features added that take a long time before they become a seamless part of the core product. While Redshift has some of these capabilities, they're nowhere near as seamless and well integrated as they are in Snowflake. By this I mean the additional features such as the marketplace, data sharing, Snowpark, etc. Snowflake is more of a packaged "data cloud" solution based around a DWH as its core. You can do a lot with one that you can with the other, and your preference may depend on many factors: cost, operational overheads, integration with tooling, etc. In terms of features and capabilities there are a lot of similarities. Having used both Redshift and Snowflake at enterprise-scale, there are a few key differences that made Snowflake a better choice for my use cases.
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