Setup the Matatika platform to deliver and process your data in Amazon Redshift in minutes.
Amazon Redshift is a cloud-based data warehousing service.
Amazon Redshift allows businesses to store and analyze large amounts of data in a cost-effective and scalable way. It can handle petabyte-scale data warehouses and offers fast query performance using SQL. It also integrates with other AWS services such as S3, EMR, and Kinesis. With Redshift, businesses can easily manage their data and gain insights to make informed decisions.
The endpoint URL for the Amazon Redshift cluster.
The port number on which the Amazon Redshift cluster is listening.
The name of the Amazon Redshift database to connect to.
The user name to use when connecting to the Amazon Redshift cluster.
The password to use when connecting to the Amazon Redshift cluster.
The name of the Amazon S3 bucket where the data to be loaded into Amazon Redshift is stored.
The default schema to use when loading data into Amazon Redshift.
The name of the AWS profile to use when connecting to Amazon Redshift.
The access key ID for the AWS account that owns the Amazon S3 bucket.
The secret access key for the AWS account that owns the Amazon S3 bucket.
The session token for the AWS account that owns the Amazon S3 bucket.
The ARN of the AWS Identity and Access Management (IAM) role to use when loading data into Amazon Redshift.
The access control list (ACL) to apply to the Amazon S3 objects being loaded into Amazon Redshift.
The prefix to apply to the Amazon S3 object keys being loaded into Amazon Redshift.
Additional options to use when loading data into Amazon Redshift.
The number of rows to load into Amazon Redshift at a time.
Whether to flush all streams to Amazon Redshift before disconnecting.
The number of streams to use when loading data into Amazon Redshift.
The maximum number of streams to use when loading data into Amazon Redshift.
The permission to use when selecting data from the default target schema.
A mapping of source schema names to target schema names.
Whether to disable the table cache when loading data into Amazon Redshift.
Whether to add metadata columns to the Amazon Redshift table being loaded.
Whether to perform a hard delete when deleting data from Amazon Redshift.
The maximum level of data flattening to perform when loading data into Amazon Redshift.
Whether a primary key is required when loading data into Amazon Redshift.
Whether to validate records before loading them into Amazon Redshift.
Whether to skip updates when loading data into Amazon Redshift.
The compression type to use when loading data into Amazon Redshift.
The number of slices to use when loading data into Amazon Redshift.
The directory to use for temporary files when loading data into Amazon Redshift.
Collect and process data from 100s of sources and tools with Amazon Redshift.