The AWS Datalake destination connector allows you to sync data to AWS. It will write data as JSON files in S3 and update the Glue data catalog so that the data is available throughout other AWS services such as Athena, Glue jobs, EMR, Redshift, etc.
The Glue tables will be created with schema information provided by the source, i.e : You will find the same columns and types in the destination table as in the source.
|Full Refresh Sync||Yes|
|Incremental - Append Sync||Yes|
To use this destination connector, you will need:
A AWS account
A S3 bucket where the data will be written
A AWS Lake Formation database where tables will be created (one per stream)
AWS credentials in the form of either the pair Access key ID / Secret key ID or a role with the following permissions:
- Writing objects in the S3 bucket
- Updating of the Lake Formation database
See the setup guide for more information about the creation of the resources.
Creating an AWS account
Feel free to skip this section if you already have an AWS account.
You will find the instructions to setup a new AWS account here.
Creating an S3 bucket
Feel free to skip this section if you already have an S3 bucket.
You will find the instructions to create an S3 bucket here.
Creating a Lake Formation Database
Feel free to skip this section if you already have a Lake Formation Database.
You will find the instructions to create a Lakeformation Database here.
The AWS Datalake connector lets you authenticate with either a user or a role. In both case, you will have to make sure that appropriate policies are in place.
Feel free to skip this section if you already have appropriate credentials.
Option 1: Creating a user
You will find the instructions to create a user here. Make sure to select "Programmatic Access" so that you get secret access keys.
Option 2: Creating a role
You will find the instructions to create a role here.
Assigning proper permissions
The policy used by the user or the role must have access to the following services:
- AWS Lake Formation
- AWS Glue
- AWS S3
You can use the AWS policy generator to help you generate an appropriate policy.
Please also make sure that the role or user you will use has appropriate permissions on the database in AWS Lakeformation.
Setup the AWS Datalake destination in Airbyte
You should now have all the requirements needed to configure AWS Datalake as a destination in the UI. You'll need the following information to configure the destination:
- Aws Account Id : The account ID of your AWS account
- Aws Region : The region in which your resources are deployed
- Authentication mode : "ROLE" if you are using a role, "USER" if using a user with Access key / Secret Access key
- Target Role Arn : The name of the role, if "Authentication mode" was "ROLE"
- Access Key Id : The Access Key ID of the user if "Authentication mode" was "USER"
- Secret Access Key : The Secret Access Key ID of the user if "Authentication mode" was "USER"
- S3 Bucket Name : The bucket in which the data will be written
- Target S3 Bucket Prefix : A prefix to prepend to the file name when writing to the bucket
- Database : The database in which the tables will be created