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*If you already know how development branches work in general and want to create and start using your first branch,
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*If you already know how development branches work in general and want to create and start using your first branch,
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go to our [Getting Started tutorial](/tutorial/branches/).*
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Development Branches allow you to modify [component configurations](/components/) without interfering with running
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configurations or entire [orchestrated pipelines](/flows/orchestrator/). They are ideal to use when making bigger changes
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to a project or when you need to be extra careful about performing your changes safely.
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Development Branches allow you to modify [component configurations](/components/) without interfering with running
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configurations or entire [orchestrated pipelines](/flows/orchestrator/). They are ideal to use when making bigger changes
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to a project or when you need to be extra careful about performing your changes safely.
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To give an example, let's say that you have an ordinary orchestration that extracts, transforms and writes data
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to a target system, and you need to remove a column from the source. To do that, you must modify several configurations,
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and ideally, also perform a dry run to check that the data in the target system is correct. However, modifying a pipeline
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that runs, e.g., every ten minutes, is difficult without an outage of the pipeline. Development Branches are designed
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To give an example, let's say that you have an ordinary orchestration that extracts, transforms and writes data
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to a target system, and you need to remove a column from the source. To do that, you must modify several configurations,
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and ideally, also perform a dry run to check that the data in the target system is correct. However, modifying a pipeline
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that runs, e.g., every ten minutes, is difficult without an outage of the pipeline. Development Branches are designed
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to help in such situations.
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{% include public-beta-warning.html %}
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## How Branches Work
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When you create a development branch in your project, you obtain an exact copy of the project and all its current
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configurations. You can then modify these configurations without ever touching the original ones in production,
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and these will keep running in orchestrations.
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When you run a configuration in a branch, it can **read** the [tables](/storage/tables/) and [files](/storage/files/)
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When you create a development branch in your project, you obtain an exact copy of the project and all its current
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configurations. You can then modify these configurations without ever touching the original ones in production,
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and these will keep running in orchestrations.
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When you run a configuration in a branch, it can **read** the [tables](/storage/tables/) and [files](/storage/files/)
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from Storage as if it were a normal configuration. However, when your branch configuration attempts to **write** data
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(tables or files), the data is written to the branch’s isolated storage layer. This means that production data and branch data
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(tables or files), the data is written to the branch's isolated storage layer. This means that production data and branch data
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are completely separated. There is no need to duplicate your entire project's data when creating a new branch.
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### Branched Storage Architecture
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## Branched Storage
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Branched Storage is an improved storage isolation model for development branches. Instead of cluttering your project
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with prefixed bucket names (like `in.c-1234-bucket`), each branch gets its own fully isolated storage namespace.
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Production data is never touched, and no data is copied up front — a copy is created only when you actually write to or modify a table within the branch.
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{% include tip.html content="Branched Storage is available for projects running on <strong>Snowflake</strong>. If your project uses BigQuery, the classic prefix-based model still applies — Branched Storage support for BigQuery is coming." %}
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Instead of creating prefixed buckets immediately upon branch creation, Keboola now uses *branched storage* —
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a dedicated storage namespace that behaves like an isolated copy of your production environment,
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but without duplicating data up front. Tables and files are only materialized when they are cloned or written to.
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The isolation is handled by automatically prefixing schema names, without injecting branch IDs into bucket names.
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### Why It Matters
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This approach provides:
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-**Full isolation** – each branch has its own Storage environment that does not affect production.
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-**On-demand materialization** – tables and files appear in the branched storage only once they are accessed, cloned, or written to within the branch.
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-**Transparent behavior** – from the user’s perspective, reading and writing works exactly the same as in production.
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When a job in a branch reads from a table that has not been modified, the data is transparently loaded from production.
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-**Safety** – all write operations are performed within the branch’s own isolated context, ensuring that production data remains untouched.
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Without Branched Storage, every write in a branch produced new buckets with prefixed names that were visible in
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production Storage and cluttered the namespace. You had to be careful about what you ran and where.
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<divclass="alert alert-info"markdown="1">
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Branched Storage is currently available **only for projects using Snowflake** as the backend.
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Projects running on **BigQuery** continue to use the previous branch model with prefixed buckets (e.g., `in.c-1234-bucket`) until Branched Storage support is added.
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</div>
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With Branched Storage:
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-**Production is safe** — writes in a branch never affect production data.
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-**No data duplication up front** — creating a branch is instant and doesn't copy your storage. Tables are only materialized when you write to them.
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-**Reads are transparent** — if a table hasn't been modified in the branch, you're reading live production data, with no extra cost.
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-**Clean Storage** — the branch has its own storage namespace. No prefixed buckets visible in production.
Once enabled, all new branches in that project will automatically use the isolated storage model.
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### How It Behaves in Practice
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When you create a data source connector and then transform the data it produces using a transformation, it behaves the following way in branches:
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When you create a branch and run a job:
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In production, you might have a data source connector that extracts website requests data to a bucket called `in.c-requests`. Then you create a transformation that takes data from `in.c-requests` and transforms it into aggregated visits stored in `out.c-visits`. Both buckets contain production data.
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1.**Reading** from a table that hasn't been modified → the branch reads directly from production. Nothing is copied.
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2.**Writing** to a table for the first time → the table is cloned into the branch's isolated storage. All subsequent reads and writes for that table within the branch use this isolated copy.
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3.**Production is never touched** — regardless of how many times you write in a branch.
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When you switch to a new branch in a **Snowflake project**, no data is copied immediately. The branched storage references production data until you start modifying or writing data.
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When you delete or merge the branch, the branched storage is cleaned up accordingly.
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If you run a transformation that writes to a new table or modifies existing data, the table will be created or cloned inside the branched storage.
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Any subsequent reads or writes within that branch will operate only on this isolated copy. Your production data in `out.c-visits` remains untouched.
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## Data Pipelines in Branches
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For **BigQuery projects**, the classic prefix-based model still applies — new tables written from a branch are prefixed with the branch ID (e.g., `out.c-1234-visits`).
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In production, you might have a data source connector that extracts data into a bucket `in.c-requests`, and a transformation
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that reads from it and writes results to `out.c-visits`.
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<divclass="alert alert-info"markdown="1">
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In Branched Storage (Snowflake), data is materialized only when it is written to or cloned within a branch.
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Reading from unmodified tables uses production data transparently.
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</div>
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When you switch to a branch on a **Snowflake project with Branched Storage enabled**, no data is copied immediately.
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The branch reads from production Storage until you run a job that writes data — at that point, only the affected tables
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are materialized in the branch's own storage. Your production `out.c-visits` remains untouched throughout.
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This allows you to test the entire pipeline with real data, in complete isolation from production, without duplicating all storage content at branch creation.
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This allows you to test the entire pipeline with real data, in complete isolation from production, without duplicating
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all storage content at branch creation.
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## Creating a Branch
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If you have your configurations ready in production and want to create a branch to test some changes, click on your project’s name
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at the top of the screen. Then click on the green icon **New** displayed next to your project’s name.
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If you have your configurations ready in production and want to create a branch to test some changes, click on your project's name
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at the top of the screen. Then click on the green icon **New** displayed next to your project's name.
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{: .image-popup}
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@@ -90,19 +102,20 @@ Name your new branch and click **Create Development Branch** to open it.
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The branch will appear right below the name of your production project.
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{: .image-popup}
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.
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Now you can start modifying your configurations, run them, and analyze the results.
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Now you can start modifying your configurations, run them, and analyze the results.
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If you want to learn more about working in a branch, follow our [tutorial](/tutorial/branches/).
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## Closing a Branch
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Before you merge your development branch back to production, check a detailed [diff of the configuration changes](/tutorial/branches/project-diff/).
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Before you merge your development branch back to production, check a detailed [diff of the configuration changes](/tutorial/branches/project-diff/).
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You can end your branch's lifecycle in two ways:
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-**Deleting**-- if you do not wish to use the changes you've made and want to simply discard them. The data associated with the branch is discarded when the branch is deleted.
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-[**Merging into production**](/tutorial/branches/merge-to-production/)-- all changes in the configurations are brought back to the respective production configurations. All the changes are applied at once (after you approve them) and produce new [versions](/components/#configuration-versions) of the respective configurations. The branch can be either deleted or kept for further reference after merging.
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-**Deleting**— if you do not wish to use the changes you've made and want to simply discard them. The data associated with the branch is discarded when the branch is deleted.
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-[**Merging into production**](/tutorial/branches/merge-to-production/)— all changes in the configurations are brought back to the respective production configurations. All the changes are applied at once (after you approve them) and produce new [versions](/components/#configuration-versions) of the respective configurations. The branch can be either deleted or kept for further reference after merging.
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***Important:** All of this happens within the same project, enabling collaboration with other project members on the modifications.*
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@@ -125,4 +138,3 @@ Components using OAuth do not allow authorizing nor changing the OAuth in a deve
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*****
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***Important:** Development branches are for development and testing only, so setting up status notifications on Flows is not supported.*
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