- Overview
- Platform setup and administration
- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
- Connecting a customer-managed data lake
- Creating an AWS IAM role for Data Bridge
- Connecting a Snowflake data warehouse
- Connecting a Redshift data warehouse (public connectivity)
- Connecting a Redshift data warehouse (private connectivity)
- Reauthorizing a Snowflake OAuth connection
- Using Snowflake with Peak
- SQL Explorer overview
- Roles and permissions
- User management
- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Supply Chain & Retail Solutions user guide
Data Bridge overview
Data Bridge connects Peak to your data lake and data warehouse so Peak can read and process data without copying it into a separate store. You control how Peak accesses your data and where data is stored.
Why use Data Bridge?
- Quicker onboarding — You do not need to configure multiple data interfaces. Fewer data feeds need to be scheduled, and data is available in Peak as soon as it has been stored.
- Security — You have full control over how your data is accessed and who can access it. Data is not exposed to the public internet; for example, customer-managed Amazon S3 data is transferred securely via AWS PrivateLink.
- No data duplication — Data is not replicated across multiple locations, making it easier to maintain and helping to ensure data integrity.
- Flexibility — You can store your data in any format and use it in any way you see fit.
- Data localization compliance — Data is stored on your infrastructure, which helps you meet your specific data localization requirements.
Data lake and data warehouse
Peak uses two types of data stores:
- Data lake: Stores structured and unstructured data in raw form. Peak supports Amazon S3.
- Data warehouse: Stores structured, processed data for analytics. Peak supports Snowflake and Amazon Redshift.
A data warehouse connection is required for features such as Data Sources and SQL Explorer.
Supported configurations
Peak supports Peak-managed and customer-managed storage. The available combinations are shown below.
| Data lake ownership | Data lake type | Data warehouse ownership | Data warehouse type |
|---|---|---|---|
| Peak-managed | Amazon S3 | Peak-managed | Amazon Redshift |
| Peak-managed | Amazon S3 | Peak-managed | Snowflake |
| Customer-managed | Amazon S3 | Peak-managed | Amazon Redshift |
| Peak-managed | Amazon S3 | Customer-managed | Snowflake |
| Customer-managed | Amazon S3 | Peak-managed | Snowflake (read-only share) |
| Customer-managed | Amazon S3 | Customer-managed | Snowflake |
Peak-managed Amazon S3 and Peak-managed Amazon Redshift
Peak owns and manages both the data lake and data warehouse. The Peak platform connects to your infrastructure and ingests data into both. This is the default configuration for new customers who do not have existing data infrastructure on Peak.
Customer-managed Amazon S3 and Peak-managed Amazon Redshift
Suitable if you have an existing Amazon S3 data lake that you want to use with Peak. You own and manage the data lake, and Peak owns and manages the data warehouse within the Peak environment.
Peak-managed Amazon S3 and customer-managed Snowflake
Suitable if you have an existing Snowflake data warehouse that you want to use with Peak. You own and manage the Snowflake data warehouse, and Peak owns and manages the data lake. After onboarding, Peak has read-only access to the schema containing your raw data, and read-write access to a separate schema that Peak writes data back to.
Peak-managed Amazon S3 and Peak-managed Snowflake (with read-only Snowflake share)
Suitable if you have a Snowflake data warehouse but do not want to share connection details with Peak. Peak owns and manages both the data lake and data warehouse, and you create a share between your Snowflake account and Peak's. Shared data objects are read-only and cannot be modified.
Customer-managed Amazon S3 and Peak-managed Snowflake (with read-only Snowflake share)
Suitable if you have both an Amazon S3 data lake and a Snowflake data warehouse but do not want to share connection details with Peak. Peak owns and manages the data warehouse, and you give Peak read-only access to your S3 data lake and create a Snowflake share. Shared data objects are read-only and cannot be modified.
How Data Bridge connects to your storage
graph TD
Peak[Peak platform]
Bridge[Data Bridge]
S3[Customer Amazon S3 data lake]
DW[Customer data warehouse]
IAM[IAM role and policy]
PrivateLink[AWS PrivateLink]
Peak --> Bridge
Bridge --> S3
Bridge --> DW
IAM --> S3
PrivateLink --> S3
graph TD
Peak[Peak platform]
Bridge[Data Bridge]
S3[Customer Amazon S3 data lake]
DW[Customer data warehouse]
IAM[IAM role and policy]
PrivateLink[AWS PrivateLink]
Peak --> Bridge
Bridge --> S3
Bridge --> DW
IAM --> S3
PrivateLink --> S3
This diagram summarizes the secure connection path for customer-managed Amazon S3. Peak uses the IAM role you provide to access specific storage paths.
- Why use Data Bridge?
- Data lake and data warehouse
- Supported configurations
- Peak-managed Amazon S3 and Peak-managed Amazon Redshift
- Customer-managed Amazon S3 and Peak-managed Amazon Redshift
- Peak-managed Amazon S3 and customer-managed Snowflake
- Peak-managed Amazon S3 and Peak-managed Snowflake (with read-only Snowflake share)
- Customer-managed Amazon S3 and Peak-managed Snowflake (with read-only Snowflake share)
- How Data Bridge connects to your storage