Architecture Design for Data Warehouse & Lakehouse Scenarios
We design scalable analytics architectures based on Amazon Redshift — optimized for performance, security, and cost efficiency within the AWS ecosystem.
Amazon Redshift – Cloud Data Warehouse for Modern Analytics and Lakehouse Scenarios
From traditional data warehousing to open lakehouse architectures, Redshift combines performance, scalability, and seamless integration within the AWS stack — now with native support for open formats and semi-structured data.
How We Support You with Redshift
We guide you from the initial analysis to a scalable lakehouse architecture — with solutions designed to deliver quick results and long-term impact.
Integration with AWS Services
Seamless connection of Redshift with Amazon S3, AWS Glue, Lake Formation, and Kinesis to automate and streamline data flows efficiently.
Performance tuning & cost optimization
We analyze and optimize queries, storage structures, and workload management to make your Redshift environment faster and more cost-efficient.
Migration of existing data warehouses
Secure migration of existing DWH systems to Amazon Redshift—including schema transfer, data integration, and validation of your pipelines.
Automation of data pipelines
Automated ELT processes with dbt, Qlik Talend Cloud, Apache Airflow, or AWS Step Functions ensure robust and reproducible data processing.
Data Governance & Security
Implementation of data governance structures, access controls, and security policies based on AWS Lake Formation and IAM — ensuring compliance and transparency.
Our AWS Redshift consulting services at a glance
From targeted performance optimization to complete lakehouse architecture: we support you with modular services that can be flexibly integrated into your AWS strategy.
Amazon Redshift Performance Boost – More Power, Lower Cost
We analyze your Redshift cluster, identify bottlenecks, and maximize performance and efficiency.
This helps you accelerate queries, reduce operational costs, and use Redshift as it’s meant to be — fast, scalable, and cost-effective.
Architecture Assessment for Amazon Redshift
We evaluate the structure, integration, and workflows of your existing analytics environment and show you how to leverage Redshift as the core of your AWS data platform.
Whether it’s a traditional data warehouse or a modern lakehouse, you’ll receive a clear roadmap for your cloud architecture.
Amazon Redshift Performance Boost – More Power, Lower Cost
We analyze your Redshift cluster, identify bottlenecks, and maximize performance and efficiency.
This helps you accelerate queries, reduce operational costs, and use Redshift as it’s meant to be — fast, scalable, and cost-effective.
Architecture Assessment for Amazon Redshift
We evaluate the structure, integration, and workflows of your existing analytics environment and show you how to leverage Redshift as the core of your AWS data platform.
Whether it’s a traditional data warehouse or a modern lakehouse, you’ll receive a clear roadmap for your cloud architecture.
Amazon Redshift as the central platform in the AWS tool stack
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FAQs AWS
Yes through support for semi-structured data (e.g., JSON) and direct processing of files stored in S3.
Both are cloud data warehouses, but Redshift is more deeply integrated into the AWS ecosystem, while Snowflake offers greater cross-cloud flexibility.
Yes with Redshift Spectrum and integration into AWS Lake Formation, data in the data lake can be queried directly without ETL.