> For the complete documentation index, see [llms.txt](https://docs.bdb.ai/pre-sales/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bdb.ai/pre-sales/manufacturing-use-case/technical-requirements/data-store-data-lake.md).

# Data Store(Data Lake)

* [x] **Requirement**: Data platform should have the provision for a Data Lake with a storage tier able to store all (structured, semi-structured and unstructured) data in a cost-effective way while the platform should be horizontally scalable. 

* [x] **BDB Response:** Data Lake is outside the BDB platform and having capability for configuring customer’s choice data lake. \
  MongoDB is recommended for Data Lake.

* [x] **Requirement:** Data Lake should have data zones categorized into Staging Layer (Raw Data), Curated Layer (Cleansed Data) and Processed Layer (transformed data). There should be provision for creating a sandbox layer within the data lake for running analytical workloads. 

* [x] **BDB Response**: Yes, MongoDB supports/enables to categorize data zones, also it provisions for creating a sandbox layer within the data lake for running analytical workloads.

* [x] **Requirement**: Data Lake architecture should have Storage and Compute nodes decoupled which can be scaled up/down as needed. 

* [x] **BDB Response**: Yes, Data Lake architecture will be designed to have storage and compute nodes decoupled. 

* [x] **Requirement:** Tiered storage architecture shall support storing Infrequently accessed data to be archived and stored in an archive-based storage in a cost-effective manner. 

* [x] **BDB Response**: Yes, Data Lake supports tiered storage architecture for storing Infrequently accessed data to be archived and stored in an archive-based storage in a cost-effective manner.

* [x] **Requirement**: Provision of Querying the data directly from data lake without moving the data to Enterprise Datawarehouse.

* [x] **BDB Response**: Yes, BDB Platform has provision of Querying the data directly from data lake without moving the data to Enterprise Datawarehouse.