Snowflake: Making Mainframe Data Available on Snowflake

Blog > Big Data > Making Mainframe Data Available on Snowflake

Making Mainframe Data Available on Snowflake

Authors Photo Peter Coppenrath | May 13, 2020

I don’t like to admit how long it took me to embrace the cloud. Fortunately for me, I was already a cloud believer by the time I saw Snowflake, so I was ready to appreciate what a game changer it was.

I would not say I was an early adopter of the cloud. I understood the compute power available in the cloud, but I saw it as an environment for “new” data, not the place where you put your most valuable enterprise data. That type of data — critical enterprise data — was on premises, often residing in the mainframe. And that is not going to change. Mainframes are going to remain at the center of many critical IT operations for the foreseeable future. They just work too well to be replaced right now.

However, this does not mean that data on the mainframe can’t be brought to the cloud for analytics. The cloud is the focal point of new IT initiatives, and mainframe data will be part of those initiatives.

Bringing mainframe data to Snowflake

Snowflake is a data warehouse that makes full use of the advantages of the cloud without compromise because it has no debt to an on-premises architecture. Storage and compute are decoupled and each individually scalable without any prior planning. At the same time, you can access all of this with SQL, which means you could start without learning significant new skills. And any existing work you had done elsewhere is readily ported over. It can be as good or better than any highly curated on-premises solution while at the same time being cost effective and have zero administration overhead.

As capable as Snowflake is, like many modern platforms it still can’t make use of raw mainframe data. The data needs to be transformed before it can be consumed.

How Precisely can help

Making mainframe data accessible outside the mainframe is something Precisely has been doing for decades. We started with mainframe style sorting on UNIX, but over time extended our capabilities to deliver ready-to-use data to Splunk and Hadoop. You could say we are the “go to” experts for getting your mainframe data into modern analytical solutions.

Precisely supports Snowflake to deliver transformed mainframe data directly to the platform. Snowflake isn’t tied to a particular cloud vendor and neither is our solution.

Using Connect, developers can source, transform and load mainframe data to Snowflake within a single flow. Once the data lands in Snowflake it is entirely indistinguishable from other data source and immediately ready use in existing or new processes.

To learn more, what our webcast: Real-Time Data Replication to Snowflake