← Part 1: Your SAP Data Is Already Real-Time

Last week the forecasting team at our Mittelstand walked away with something they'd never had: a fresh, validated, DuckDB-native view of every order line and customer record they cared about, no warehouse landing in sight. Latency under five minutes, anomalies caught at the gate. Good ergonomics. Good numbers.

Then the AI engineer asked the question that always comes next.

"Great. How does the agent reach this?"

Picture a forecasting team at an industrial-controls Mittelstand. Their job for the next quarter: launch an AI-driven inventory and demand-forecasting tool that the operations team will actually trust enough to act on. They have the model. They have the GPUs. They cannot ship.

The reason: their nightly ETL job runs at 02:00 and finishes around 04:00, by which point the model trains on data that's already half a day old. By the time the forecast reaches the procurement system at 08:00, it's reasoning about a world that existed fourteen hours ago. When the CFO asks why the model recommended ordering more of an item that just sold out at lunchtime, nobody has a good answer — because the data the model saw never knew the lunchtime existed.

The fix isn't a better ETL. The fix is removing the ETL.

ERPL started as a DuckDB extension for SAP. That's still its center of gravity. But over the past few months it grew arms — into Microsoft 365, into Microsoft Dynamics 365, into the rest of the modern enterprise data surface.

Today's update to erpl.io makes that official. The landing page now reflects what ERPL has quietly become: a SQL gateway to your whole enterprise stack.

We built erpl-adt because we got tired of Eclipse being the only way to interact with ABAP systems programmatically. If you wanted to search objects, read source code, or run unit tests against SAP — you had to use Eclipse ADT. No CLI, no scriptable API client, nothing you could plug into a CI pipeline or hand to an AI agent.

So we built one. A single binary that speaks the ADT REST API, works from the command line, and doubles as an MCP server for AI coding agents.

Summary​

This article compares ERPL's approach to SAP integration with traditional methods, highlighting performance improvements, ease of use, and cost benefits. We'll examine real-world scenarios and provide concrete examples of how ERPL transforms SAP data integration workflows.

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Learn how to build real-time SAP dashboards using ERPL and DuckDB. This comprehensive guide covers everything from data extraction to dashboard creation, including practical examples and best practices for monitoring your SAP systems in real-time.

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Discover how ERPL transforms SAP data integration for data science workflows. This comprehensive guide covers everything from data extraction to machine learning model deployment, showing how ERPL enables data scientists to work directly with SAP data using familiar tools and frameworks.

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DuckDB is a high-performance SQL OLAP database system known for its efficiency in handling analytical queries. However, accessing and analyzing public holiday data across different countries and date ranges can be challenging. By leveraging the ERPL-Web extension, you can seamlessly fetch and process this data within DuckDB.

We demonstrate how to retrieve public holiday data for Germany, showcasing the ease and power of this approach. This example highlights how DuckDB and ERPL-Web can streamline your data workflows by connecting your SQL environment with external data sources efficiently.

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This article demonstrates how to integrate SAP BW data in Microsoft Fabric using ERPL, providing a comprehensive guide for connecting enterprise SAP systems to Microsoft's modern data platform.

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• Airbyte is one of the most popular integration solutions. However it is lacking access to enterprise data sources from SAP. We show how with our ERPL Airbyte connector one can bridge this gap.

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• The article guides on integrating Excel with Parquet files using DuckDB, highlighting the efficiency of DuckDB for large data sets and how it surpasses Excel's normal data handling limits.
• It includes step-by-step instructions for installing the DuckDB ODBC driver, configuring Excel, setting up the ODBC connection, and suggests using Power Query Desktop for data transformation.