---
title: Store Composite
description: A Store Composite prepares data in the Store layer with joins, filters, expressions and aggregations on Stages or other Store Composites.
---

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# Store Composite

**Applies to**  
Platform: Microsoft SQL Server · Snowflake · Databricks · Fabric Lakehouse · Fabric Warehouse · Oracle  
Architecture: Data Store

A Store Composite prepares data in the Store layer with joins, filters, expressions and aggregations on Stages or other Store Composites. Use it for an intermediate result that a Store Entity or another Store Composite reads. By default it is a view; with Implementation Type `Cached` it is a table that each load empties and refills.

### Sources and relationships

A Store Composite reads [Stages](https://knowledge.bigenius-x.com/create-a-stage?hsLang=en) and other Store Composites in exactly one dataflow. It has no relationships. A [Store Entity](https://knowledge.bigenius-x.com/create-a-store-entity?hsLang=en) or another Store Composite reads its result view.

### Create a Store Composite

- With the wizard: open the menu of a Stage or Store Composite, choose **Automate** and then **Create Store Composite**. Its steps are [Create Model Object](https://knowledge.bigenius-x.com/wizard-step-create-model-object?hsLang=en), [Create Dataflow](https://knowledge.bigenius-x.com/wizard-step-create-dataflow?hsLang=en), [Map Selected Terms](https://knowledge.bigenius-x.com/wizard-step-map-selected-terms?hsLang=en) and [Add to View](https://knowledge.bigenius-x.com/wizard-step-add-to-view?hsLang=en). See [Create a Model Object with the wizard](https://knowledge.bigenius-x.com/create-a-model-object-with-the-wizard?hsLang=en).
- Manually: [create a model object](https://knowledge.bigenius-x.com/create-a-model-object?hsLang=en) of type Store Composite in the Data Store column, [create a dataflow set](https://knowledge.bigenius-x.com/create-a-data-flow-set?hsLang=en), [add the source model objects](https://knowledge.bigenius-x.com/add-a-model-object-into-a-data-flow-set?hsLang=en) and [map the terms](https://knowledge.bigenius-x.com/map-a-source-term-with-a-target-term?hsLang=en).

Then add joins, a where clause or expressions to the dataflow sets as the composite needs.

### Properties

- [Implementation Type](https://knowledge.bigenius-x.com/implementation-type-model-object?hsLang=en): `Virtual` (default) creates views only, so every query reads the current Stage data. `Cached` adds a table that the loader empties and refills on every load.
- [Deduplication Method](https://knowledge.bigenius-x.com/deduplication-method-model-object?hsLang=en): `None` (default), `Distinct` or `Partition`, with [Sort Order within Partition](https://knowledge.bigenius-x.com/deduplication-partition-model-object?hsLang=en). A method other than `None` adds a deduplication view.

### Default Terms

- [`BG_LoadTimestamp`](https://knowledge.bigenius-x.com/bg_loadtimestamp?hsLang=en): with `Cached`, the loader writes the timestamp of the load. With `Virtual`, the term is NULL unless you map it.
- [`BG_SourceSystem`](https://knowledge.bigenius-x.com/bg_sourcesystem?hsLang=en): the source system of the row; empty unless you map it.

### Generated objects

These are the names on Microsoft SQL Server for a Store Composite `large_branch`:

| Role | Generated name | Purpose |
| --- | --- | --- |
| Source | `DS_SC_large_branch_Source` | Joins, filters and maps the sources |
| Deduplication | `DS_SC_large_branch_Deduplication` | Removes duplicate rows |
| Loader | `DS_SC_large_branch_Loader` | Empties and refills the table |
| Storage | `DS_SC_large_branch` | Composite table |
| Result | `DS_SC_large_branch_Result` | View read by the next model object |

- The loader is a stored procedure; `DS_SC_large_branch` is a table; all other objects are views.
- The deduplication view exists only with a Deduplication Method other than `None`.
- The loader and the table exist only with `Cached`.

The dependencies are:

```
Virtual: sources -> _Source -> _Deduplication -> _Result
Cached:  sources -> _Source -> _Deduplication -> _Loader
         _Loader -> DS_SC_large_branch -> _Result
```

### Example

The Store Composite `large_branch` on Microsoft SQL Server keeps only the large branches of the Stage `branch`. It has the default Implementation Type `Virtual` and maps the business terms of the Stage; `BG_LoadTimestamp` is not mapped. Its dataflow set has this where clause, in which `s1` is the alias of the Stage:

```
s1.MARKET_SIZE = 'large'
```

The generated source view ends with:

```
FROM [<database name>].[stg].[STG_ST_branch_Result] AS [s1]
WHERE [s1].[MARKET_SIZE] = 'large'
```

`<database name>` is the Stage database you set before deployment, and `stg` is the Stage schema of the example. The Stage `branch` holds three branches after load 1 and two after load 2:

- Load 1: 1 Basel `large`, 2 Bern `small`, 3 Zurich `large`.
- Load 2: Zurich is deleted, and Bern changes to `large`.

### Check the result

Query the result view, here in the schema `ds`:

```
SELECT BRANCH_ID, BRANCH_NAME, MARKET_SIZE
FROM ds.DS_SC_large_branch_Result
ORDER BY BRANCH_ID;
```

After load 1:

```
BRANCH_ID  BRANCH_NAME  MARKET_SIZE
1          Basel        large
3          Zurich       large
```

After load 2 of the Stage; a `Virtual` Store Composite has no loader:

```
BRANCH_ID  BRANCH_NAME  MARKET_SIZE
1          Basel        large
2          Bern         large
```

- Bern appears and Zurich disappears as soon as the Stage is reloaded, because the views read the result view of the Stage.
- With `Cached`, the result changes only after the loader of the Store Composite has run.

### Platform differences

- Snowflake: names are in capitals, and the table of a `Cached` Store Composite is a transient table. The load control task `DS_SC_<model object name>_TASK` calls its loader. The dataflow properties [Use Stream](https://knowledge.bigenius-x.com/use-stream-model-object?hsLang=en) and Warehouse Placeholder Variable Name apply.
- Databricks and Fabric Lakehouse: the loader is the notebook `DS_SC_<model object name>_Loader`. The properties [File Format](https://knowledge.bigenius-x.com/file-format-model-object?hsLang=en), [Optimization Method](https://knowledge.bigenius-x.com/optimization-method-model-object?hsLang=en) and [Optimization Method Columns](https://knowledge.bigenius-x.com/optimization-method-columns-model-object?hsLang=en) apply.
- Fabric Warehouse: the same objects as on Microsoft SQL Server.
- Oracle: names are in capitals, and the loader is a PL/SQL package. Physical properties such as Partition Clause, Table Compression and tablespaces apply.

### Limitations

- A Store Composite has exactly one dataflow and no relationships.
- An aggregation must be defined in all dataflow sets or in none.
- A Store Composite keeps no history; it has no validity terms.

### Related articles

- Previous: [Stage](https://knowledge.bigenius-x.com/create-a-stage?hsLang=en)
- Next: [Store Entity](https://knowledge.bigenius-x.com/create-a-store-entity?hsLang=en)
- Reference: [Implementation Type (Model Object)](https://knowledge.bigenius-x.com/implementation-type-model-object?hsLang=en), [Deduplication Method (Dataflow)](https://knowledge.bigenius-x.com/deduplication-method-model-object?hsLang=en), [Sort Order within Partition (Dataflow)](https://knowledge.bigenius-x.com/deduplication-partition-model-object?hsLang=en), [BG\_LoadTimestamp](https://knowledge.bigenius-x.com/bg_loadtimestamp?hsLang=en), [BG\_SourceSystem](https://knowledge.bigenius-x.com/bg_sourcesystem?hsLang=en)
- See also: [Create a Model Object with the wizard](https://knowledge.bigenius-x.com/create-a-model-object-with-the-wizard?hsLang=en), [Model a Data Store Solution](https://knowledge.bigenius-x.com/model-a-data-store-solution?hsLang=en)

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