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Copy file name to clipboardExpand all lines: README.md
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-**Converting SQL** to a new transformation framework (e.g., stored procedures -> dbt)
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- Continuously **replicating data** from an OLTP database to OLAP data warehouse (e.g., MySQL -> Redshift)
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### Data Development Testing
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### Data Development Testing
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When developing SQL code, data-diff helps you validate and preview changes by comparing data between development/staging environments and production. Here's how it works:
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1. Make a change to your SQL code
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2. Run the SQL code to create a new dataset
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data-diff integrates with [dbt Core](https://github.com/dbt-labs/dbt-core) to seamlessly compare local development to production datasets.
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# Getting Started
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### ⚡ Validating dbt model changes between dev and prod
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Looking to use data-diff in dbt development?
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Looking to use data-diff in dbt development?
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Development testing with Datafold enables you to see the impact of dbt code changes on data as you write the code, whether in your IDE or CLI.
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Development testing with Datafold enables you to see the impact of dbt code changes on data as you write the code, whether in your IDE or CLI.
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Head over to [our `data-diff` + `dbt` documentation](https://docs.datafold.com/development_testing/cli) to get started with a development testing workflow!
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Then, we compare tables between PostgreSQL and Snowflake using the hashdiff algorithm:
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-c <columns to compare> \
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-w <filter condition>
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```
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3. Set up your configuration
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3. Set up your configuration
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You can use a `toml` configuration file to run your `data-diff` job. In this example, we compare tables between MotherDuck (hosted DuckDB) and Snowflake using the hashdiff algorithm:
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```toml
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## DATABASE CONNECTION ##
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[database.duckdb_connection]
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[database.duckdb_connection]
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driver = "duckdb"
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# filepath = "datafold_demo.duckdb" # local duckdb file example
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# filepath = "md:" # default motherduck connection example
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* Time complexity approximates COUNT(*) operation when there are few differences
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* Performance degrades when datasets have a large number of differences
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</details>
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</details>
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<br>
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For detailed algorithm and performance insights, explore [here](https://github.com/datafold/data-diff/blob/master/docs/technical-explanation.md), or head to our docs to [learn more about how Datafold diffs data](https://docs.datafold.com/data_diff/how-datafold-diffs-data).
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For detailed algorithm and performance insights, explore [here](https://github.com/datafold/data-diff/blob/master/docs/technical-explanation.md), or head to our docs to [learn more about how Datafold diffs data](https://docs.datafold.com/data_diff/how-datafold-diffs-data).
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# data-diff OSS & Datafold Cloud
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## Contributors
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We thank everyone who contributed so far!
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We thank everyone who contributed so far!
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We'd love to see your face here: [Contributing Instructions](CONTRIBUTING.md)
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