Duck taping data

The Data Lakehouse combines the flexibility of data lakes with the performance of data warehouses, offering better governance and accessibility. Imagine a ship’s hull reinforced with DuckTape: agile, adaptable, and ready to weather data storms!

Rather than coding a solution from A to Z—akin to building an entire ship without a blueprint—a hybrid approach leverages the best open-source solutions like Apache Iceberg, Delta Lake, and Presto, while integrating proven proprietary tools

By combining open-source and proprietary tools, companies can optimize costs and flexibility. Here are three examples:

• Increased profitability: An international retailer uses Delta Lake and a proprietary data warehouse to optimize stock forecasting.
• Mission achievement: A cybersecurity NGO leverages Apache Iceberg and Kubernetes to monitor threats in real time.
• Business growth: A SaaS startup combines Presto with a commercial BI tool to enhance analytics and attract more customers.

Different use cases require distinct architectural approaches tailored to specific business needs.

Real-time analytics

For real-time analytics, data lakehouses enable instant querying of massive datasets through optimized engines like Presto, Trino, or Spark, while ensuring data governance and integrity with formats like Delta Lake and Apache Iceberg.

Machine learning

In machine learning, they provide structured access to data, facilitating model training and tracking with MLflow and AutoML. Pipelines can process billions of events continuously, enabling fast and efficient decision-making.

Large-scale data management

Finally, large-scale data management is optimized with advanced storage mechanisms and automatic scalability. Whether through Snowflake, BigQuery, or Databricks, data lakehouses reduce costs while maximizing performance for companies looking to fully leverage their data.

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