Load JSON in S3 into Snowflake

Snowflake's web user interface showing a SQL query being evaluated and the tabular results thereof.

With REFORM and Snowflake you can make your JSON in S3 available for analysis in minutes.

Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics.

JSON is not a normal tabular data format. Unlike tabular data the structure of each piece of JSON is tailored to a specific purpose. For example a piece of JSON for a form about you and your pets would have a very different structure to a piece of JSON for a manufacturing dashboard. Snowflake expects standard tabular data. In order to warehouse JSON data and use it to find insights we need to transform it into meaningful tables.

A screenshot of REFORM. The structure of a JSON dataset is presented as a filesystem which is being browsed and from which relational columns are being picked

REFORM lets you load JSON in S3 into tables in Snowflake. Simply provide the details of the buckets, browse even the most complex data as if it were a file browser and pick what you're interested in. Finally provide the details of an S3 bucket along with your Snowflake database, warehouse, account, username and password and REFORM will transform your data into analytic ready tables in Snowflake.

Snowflake's web user interface showing a pie chart on a laptop on a wooden desk alongside a Snowflake mug and two plants amongst other things.

REFORM supports datasets of all sizes even if they are too large to fit onto a single computer. Your data will stream from JSON in S3 thorugh REFORM and into analytic ready tables in Snowflake.