DATAFOLD FOR DATA MIGRATIONs
Migrate your data faster without compromising data quality
Plan, translate, and validate data across systems seamlessly using column-level lineage, SQL translation, and data diffing.
Migrate your data faster without compromising data quality
Supported databases
VALIDATE WITH SPEED
Automatically validate parity between databases
Accelerate migrations to new data warehouses and ELT frameworks to build the data stack your organization needs. Leverage Datafold’s efficient data diffing capabilities to validate parity of database objects—within the same or between different databases.
"Seeing statistics and visualizations on how new model data compares to existing model data makes it easy to verify our migration SLAs with stakeholders.”
Adam Underwood, Staff Analytics Engineer
NEW SQL DIALECT? NO PROBLEM
Translate transformations to your new SQL dialect with the click of a button
No more Googling, “DATE_TRUNC function in Snowflake”—use Datafold Cloud’s SQL Translator to take your existing transformation code to your new database’s SQL flavor.
PLAN WITH INTENTION
Prioritize and plan your migration smarter with column-level lineage.
Identify dependencies and usage for each data asset to prioritize or deprecate data for migration in the most optimal way.
Data diff
Validate migrations and analyze the discrepancies
For every table and column, Data Diff identifies differences between the old and new environments, helping you to quickly fix discrepancies and to prove the correctness to your stakeholders.
“The tool is super easy to use and does a great job highlighting exactly where there are differences in your data in a digestible way."
Zachary Baustein, Lead Data Analyst
DON’T LET DATA VOLUME SLOW YOU DOWN
Identify data differences at any scale
Whether your tables are thousands or billions of rows, Datafold catches data differences with efficiency. Instead of manual queries across databases, leverage Datafold’s API and scheduler to run data diffs at any volume and cadence.
"No question I’d recommend Datafold for any large-scale migration."
Jon Medwig, Staff Data Engineer
