Flexible data platform as a service
Snowflake software
Snowflake makes a huge impression with the Data Cloud Platform. On the one hand, it manages to remove all installation, configuration, management and maintenance from the customer. On the other hand, it offers a simple platform with which large amounts of data can be effortlessly brought together in one database. Various actions can then be applied to this data in Snowflake. Think of data analysis, data connections and restructuring to feed other applications.
Cloud-agnostic platform from Snowflake
The Snowflake platform is cloud agnostic. Snowflake built this platform from the ground up. This makes it possible to offer Snowflake via Amazon Web Services, Google Cloud, and Microsoft Azure. The Snowflake platform is designed with standard cloud principles in mind, such as scalability and affordability. In addition, Snowflake can secure data down to the row level and meet all compliance and governance-to demand.
What can you already achieve in Snowflake software?
As a developer you can Snowflake access via an API to load, query, and analyze data. You can also use the web interface, which allows you to perform the same actions and view results directly in your browser. Snowflake relies heavily on SQL (Structured Query Language). SQL is a simple language for working with data and can be learned quickly. In the Snowflake web interface, you also need to use several SQL commands to work with Snowflake. Snowflake supports Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC) interfaces, which allow you to connect to a Snowflake database in any programming language.
Flexibility of Snowflake Data Platform
The Snowflake Data Platform is suitable for structured data such as CSV files or Excel sheets with rows and columns. However, Snowflake has adapted to the cloud era and can also handle XML and JSON datasets. This is especially useful when data from SaaS solutions must be retrieved and processed in Snowflake.
Regardless of the structure of the data, Snowflake can retrieve and filter it using SQL. It is also possible to combine data from different tables, even if it is hundreds of thousands or millions of rows.
Additionally, Snowflake recently unveiled Snowpark. Snowpark gives data analysts, data scientists, and developers the ability to write code in their favorite programming language, using familiar programming concepts. This allows them to run ETL/ELT workloads, prepare data, and add features to Snowflake.
Metadata Champion
According to Snowflake experts, Snowflake excels in metadata creation. By analyzing all the data in Snowflake and creating metadata, Snowflake performs faster than other databases. In addition, the Snowflake Data Platform has an extensive caching system that further improves performance.
In addition, Snowflake can be used in various ways. For example, to analyze existing data in the database, or to process and analyze incoming streaming data in real time. Incoming streaming data can be modeled and made suitable for an application directly. In addition, it can also be adapted to be stored more efficiently.
Contact
Curious about what else Snowflake can do? Feel free to contact our experts at Victa!
