Running Spark Jobs with Snowflake Data

Snowflake

Snowflake is a cloud-based data warehousing company that provides a platform for data storage, processing and analysis. It is considered cloud-agnostic, as it operates across Amazon Web Services (AWS), Microsoft Azure or Google Cloud. Snowflake delivers a platform that is fast, flexible, and user-friendly. It provides the means for not only data storage but also processing and analysis. One of the main reasons that Snowflake is gaining recognition as the top cloud data warehousing solution is thanks to its architecture, which consists of dynamic, scalable computing power with usage-based charges out-of-the-box features such as data cloning and sharing, on-the-fly scalable computing and third-party tool support.

Spark

Apache Spark is an open-source data processing engine that is designed to improve data-intensive applications' performance. It provides a more efficient way to process data, which can be used to speed up the execution of data-intensive tasks. It lets you process big data sets faster by splitting the work up into chunks and assigning those chunks across computational resources. Spark has been called a "general-purpose distributed data processing engine" and "a lightning-fast unified analytics engine for big data and machine learning". It provides development APIs in Java, Scala, Python, and R, and supports code reuse across multiple workloads, batch processing, interactive SQL queries, streaming analytics, machine learning, and graph processing. Spark is especially used to access and analyze social media profiles, call recordings, emails, etc. This helps companies make correct business decisions for target advertising, customer retention, fraud detection, etc.
With the growing popularity of both Snowflake for data storage and Spark for compute workloads, it is unsurprising that many organizations are seeking to run Spark jobs with Snowflake data. Kaspian offers a native connector for this operation. Just register your Snowflake datastore and link your Spark job; Kaspian's autoscaling compute layer makes it easy to crunch through any data in your cloud with minimal setup or management.
Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.

Get started today

No credit card needed