Data Lakehouse

Data Lakehouse

THe Stackable Data Platform - Architecture

Stackable for Data Lakehouses

The Stackable Data Platform offers a comprehensive solution for implementing a Data Lakehouse architecture, seamlessly combining the flexibility and scalability of a data lake with the management capabilities and structured access of a data warehouse.

The Data Lakehouse

A data lakehouse represents an innovative approach to data architecture, merging the vast data storage capabilities of data lakes with the structured querying and data management features of data warehouses. With the Stackable Data Platform, organizations can leverage Kubernetes to deploy and scale their data lakehouse architecture, ensuring flexibility, efficiency, and high availability across their data ecosystems.

The data lakehouse architecture of the Stackable Data Platform is suitable for organizations that want to use data for digital transformation and improve business agility.

Highlighed data apps from the Stackable Data Platform for DATA LAKEHOUSES

Exemplary Use Cases

  • Real-Time Decision Making: Make informed decisions instantly. Harness Apache Airflow to automate data pipelines, feeding fresh data. Combined with Trino for high-speed querying, this setup enables organizations to adapt swiftly to changing market conditions and operational demands.

  • Enhanced Customer Insights: Utilize Apache Spark for processing complex datasets and Trino for querying structured and unstructured data, supported by modern data formats like Apache Iceberg and Delta Lake. Apache Superset visualizes these insights, driving personalized customer experiences and strategic decision-making.

  • Innovative Product Development: Accelerate product innovation by utilizing the advanced analytical capabilities of Apache Spark and the seamless data querying of Trino across diverse data sources and formats. This fosters a culture of rapid experimentation and development. Also, Apache Airflow streamlines the pipeline from data collection to analysis, speeding up the iteration cycle for product development. 

  • Supply Chain Optimization: Optimize your supply chain with predictive analytics derived from e.g. streaming data. Capture real-time events and process the data with Apache Spark. Use Trino to query it, enabling dynamic adjustments to enhance efficiency and reduce operational costs.

  • Social Media Monitoring and Analysis: Ingest social media data with Apache NiFi, process it with Apache Spark, and query using Trino to gain real-time insights into market trends, customer sentiment, and brand engagement. This strategic intelligence can than enhance content strategies and brand management decisions.


Lakehouse overview

Data Lakehouse technology showcase

This demo of the Stackable Data Platform shows a data lakehouse.

It uses Apache Kafka®, Apache Nifi, Trino with Apache Iceberg and the Open Policy Agent.

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A Modern Data Lakehouse: Stackable and dbt on the TPC-H Dataset

Explore our blog post on how Stackable can be used to create a data lakehouse with

  • dbt
  • Trino
  • Apache Iceberg

Unpack the simplicity of modern ELT/ETL within a streamlined data lakehouse architecture. 


Need more Info?

Contact Sönke Liebau to get in touch with us:


Sönke Liebau

Sönke Liebau

CPO & CO-FOUNDER of Stackable

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