AWS Lake Formation vs Snowflake comparison

Snowflake is a fully managed SaaS (software as a service) that provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data.

Its platform is made up of three components:

1. Cloud services: As part of its cloud services, Snowflake uses ANSI SQL, which empowers users to optimize their data and manage their infrastructure, while Snowflake handles the security and encryption of stored data.

1. Query processing: With Snowflake, workload concurrency is never a problem because its compute layer is made up of virtual cloud data warehouses that let you analyze data through requests. Each of the warehouses do not compete for computing resources nor do they affect the performance of each other.

1. Database storage: Snowflake manages all parts of the data storage process automatically, including file size, compression, organization, structure, and metadata, as well as statistics.

Snowflake Features

Snowflake has many valuable key features. Some of the most useful ones include:

• Scalability: Snowflake architecture provides nearly unlimited scalability and high speed because it uses a single elastic performance engine. The solution also supports an unlimited amount of concurrent users and workloads, from interactive to batch.

• Automation: Snowflake makes automation easy and enables enterprises to automate data management, security, governance, availability, and data resiliency.

• Seamless cross-cloud and cross-region connections: With seamless cross-cloud and cross-region connections, Snowflake eliminates ETL and data silos. Anyone who needs access to shared secure data can get a single copy via the data cloud. In addition, Snowflake makes remote collaboration and decision-making fast and easy via a single shared data source.

• Third-party data integrations: Snowflake’s Data Marketplace offers third-party data which allows you to connect with Snowflake customers to extend workflows with data services and third-party applications.

Snowflake Benefits

There are many benefits to implementing Snowflake. Some of the biggest advantages the solution offers include:

• Helps optimize costs

• Reduces downtime

• Improves operational efficiency

• Built for high reliability and availability

• Automates data replication for fast recovery

Reviews from Real Users

Below are some reviews and helpful feedback written by PeerSpot users currently using the Snowflake solution.

Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."

A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."

A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."