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Flexibel data platform as a service
Snowflake software
Snowflake makes a huge impression with its Data Cloud Platform. On one hand, it eliminates all installation, configuration, management, and maintenance at the customer's end. On the other hand, it provides a simple platform that effortlessly brings together large amounts of data into a single database. Various actions can then be applied to this data in Snowflake, such as data analysis, data connections, and restructuring to feed other applications.
Cloud-agnostic platform by Snowflake
The Snowflake platform is cloud-agnostic. Snowflake has built this platform from the ground up, making it possible to offer Snowflake through Amazon Web Services, Google Cloud, and Microsoft Azure. When designing the Snowflake platform, standard cloud principles such as scalability and affordability were taken into account. Furthermore, Snowflake can secure data at the row level and meet all compliance and governance requirements.
What can you achieve in Snowflake software?
As a developer, you can access Snowflake via an API to load, retrieve, 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 heavily relies on SQL (Structured Query Language). SQL is a simple language for working with data and can be quickly learned. In the web interface of Snowflake, you also need to utilize various SQL commands to work with Snowflake. Snowflake supports Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC) interfaces, allowing you to connect to a Snowflake database in any programming language.
Flexibility of the 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 retrieving and processing data from SaaS solutions 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 they consist of hundreds of thousands or millions of rows.
Additionally, Snowflake recently introduced Snowpark. Snowpark allows data analysts, data scientists, and developers to write code in their favorite programming language using familiar programming concepts. This enables them to execute ETL/ELT workloads, prepare data, and add functions to Snowflake.
Metadata champion
According to Snowflake experts, Snowflake excels in creating metadata. By analyzing all the data in Snowflake and creating metadata, Snowflake performs faster than other databases. Additionally, the Snowflake Data Platform has an extensive caching system that further improves performance.
Furthermore, Snowflake can be utilized in various ways. For example, it can be used to analyze existing data in the database or process and analyze incoming streaming data in real-time. Incoming streaming data can be modeled and prepared directly for an application. Moreover, it can also be adjusted to be stored more efficiently.
Contact
Curious about what else Snowflake can do? Feel free to contact our experts at Victa!
