Coalesce is the T (Transformation) in our ITS “Automated” Modern Data Stack. We view Coalesce as the first true game-changing holistic data pipeline transformation solution for data processing for Data Warehouses, Data Lakes, Data etc. The Coalesce tool is easy to use and get started with unlike previous on-prem ETL tools that have been semi-ported to the cloud. It is also the first data transformation tool we have seen that uses a column aware architecture. Coalesce provides the best of both worlds of code and gui driven pipeline automated creation.
What does Coalesce provide to our Automated Modern Data Stack?
Coalesce provides the first automated transformation data pipeline tool we have tested that scales with Snowflake and makes the transformation of data pipelines more automated. It provides these amazing features and capabilities:
- Ease of use in creating patterned transformations.
- Extreme Transformation flexibility at both object and pipeline levels. Combined code and gui editing.
- Automation templates which can be shared across your entire data engineering team.
- Coalesce separates the BUILD and the DEPLOYMENT of data pipelines. Providing flexibility of testing your data pipeline.
- You are able to use column-aware metadata for automated creation of database objects including dimensions.
- You can easily built streaming data pipelines with Snowflake Streams and Tasks via Coalesce
- You can quickly implement patterned transformations like Deferred merge across hundreds or thousands of tables.
- Built for true cloud scale as a cloud first tool to operate on top of Snowflake.
Do you want to try Coalesce out with a free trial?
More details on Coalesce’s Transformation data engineering capabilities: Does Coalesce provide to our Automated Modern Data Stack?
What we really like:
- Separation of the BUILD and DEPLOYMENT. This provides a much easier way to test changes separately from deployment. You can easily replay and of the meta-data changes within data objects and data-pipelines. Each change within columns is committed into git. We view this feature of Coalesce to be similar to Snowflake’s write forward Micro-Partitions (that provide the architecture and tech for features like time-travel and no-copy cloning). You now are recording each change within the objects which allows you to apply the commit to any target state.
- Column-Awareness. The Column-Awareness feature tracking is similar to this as well. It allows a concept of state and history within a column (field) of data. This is a really important concept that has been missing from data integrity and pipelines until this implementation.
- Object Level flexibility.
- Easy to get started immediately to test it out. There is no software to install and no infrastructure to manage. You are up and running within minutes on Coalesce.
Reasons not to choose Coalesce as part of your Modern Data Stack?
- You are using a database that is not Snowflake.
- You like to hand code all of your data pipelines because you do not trust any vendor tools and want to have plenty of extra maintenance work to always have lots of human labor.
