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@@ -24,7 +24,7 @@ All state is persisted as append-only tables in the warehouse alongside your dat
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-**Cursor-based incremental processing.** Automatic gap detection and resume, with microbatch mode for large ranges. No external checkpoint to maintain.
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-**Ingestion and Python nodes.** Load external data with Python `@loader` functions, and run `@task`, `@asset`, and `@check` nodes as first-class members of the same DAG as your SQL models.
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See the [documentation](https://docs.sqlbuild.com) for the full feature set, including providers, lifecycle hooks, Python macros, UDFs, custom materializations, data diffs, zero-copy cloning, and virtual environments. This repository also includes a focused guide to [model and raw-query diffs](docs/query-diffs.md). To coordinate dbt and SQLBuild projects, see the [dbt compatibility guide](https://docs.sqlbuild.com/concepts/dbt-compatibility/overview).
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See the [documentation](https://docs.sqlbuild.com) for the full feature set, including providers, lifecycle hooks, Python macros, UDFs, custom materializations, data diffs, zero-copy cloning, and virtual environments. This repository also includes focused guides to[target execution limits](docs/execution-limits.md) and[model and raw-query diffs](docs/query-diffs.md). To coordinate dbt and SQLBuild projects, see the [dbt compatibility guide](https://docs.sqlbuild.com/concepts/dbt-compatibility/overview).
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