Stuttgart and Wiesbaden, 3 November 2025 – Theobald Software, a leading expert in seamless SAP integration, today announced the acquisition of bluetelligence GmbH (“bluetelligence”), a software company specializing in SAP metadata management. Through this acquisition, the two companies are combining their SAP expertise and expanding their portfolio with capabilities for metadata management and data intelligence—driving greater efficiency, accuracy, and deeper insights into SAP systems.

“The combination of Theobald Software and bluetelligence is a major step forward in providing our customers with even more comprehensive data transparency,” said Dr. Thomas Bruggner, CEO of Theobald Software. “bluetelligence’s technology is the perfect complement to our solutions. With the added dimension of metadata, our customers will be able to use, automate, document, and analyze SAP data more intelligently than ever before. This creates real value for businesses—especially in light of the growing demands driven by artificial intelligence.”

Torsten Schmidt, founder and former CEO of bluetelligence, also sees the partnership as a natural evolution: “Our expertise in SAP metadata management adds a crucial component to Theobald Software’s seamless SAP integration. Delivering the best possible customer experience in SAP environments has always been our focus, and the synergy of our software products makes that possible. Customers will benefit from a comprehensive portfolio and deeper insights based on decision-critical data.”

Schmidt, the company’s founder and former CEO, will continue to play an active and advisory role going forward.

Dr. Thomas Bruggner and Torsten Schmidt

Looking Ahead Together

Theobald Software and bluetelligence share a common vision: to continuously advance their technologies and help businesses address the challenges of digital transformation within the SAP ecosystem. Their focus lies on ensuring optimal data availability and usability—the foundation for data-driven decisions and the successful application of artificial intelligence. By combining their expertise, both companies are laying the groundwork for sustainable growth and reinforcing their technology leadership in the SAP domain. Customers will benefit from practical, innovative solutions that measurably enhance transparency, efficiency, and data intelligence.

About Theobald Software

Founded in 2004 in Stuttgart, Theobald Software is a global leader in seamless SAP integration. The company’s solutions enable the use of SAP data in virtually any third-party system—on-premises or in the cloud. Over 1,700 active customers worldwide across all industries and company sizes rely on Theobald Software’s expertise to make efficient and strategic use of their SAP data. With offices in Europe and the United States, around 60 highly qualified professionals support numerous large enterprises and mid-sized companies, including the majority of Germany’s DAX-listed corporations. Partnering with industry leaders such as SAP and Microsoft, Theobald Software is dedicated to continuously developing optimal integration solutions.

About bluetelligence GmbH

Founded in 2008 in Wiesbaden, bluetelligence develops market-leading software for documenting, analyzing, migrating, translating, and cataloguing SAP metadata. Guided by the motto “Work smarter, not harder,” its automated solutions make everyday work easier for more than 200 customers across Europe in the field of Business Intelligence.

About DKMECO

DKMECO is the official APAC partner of Theobald Software, serving clients across Asia-Pacific with end-to-end SAP data integration, business intelligence, and digital transformation solutions.
As a long-standing partner, DKMECO works closely with Theobald Software to deliver the latest SAP integration technologies and best practices to enterprises and partners throughout the region.
For all inquiries in APAC regarding Theobald Software’s portfolio—including the combined strengths with bluetelligence—please contact DKMECO directly.

The post Theobald Software Acquires SAP Metadata Management Provider bluetelligence first appeared on DKM Ecosystem.

We tried extracting data from SAP into Amazon Redshift and found that the process was not complicated, and the results were satisfying. Here, we share the specific steps to help users quickly access SAP data!

Step 1. Create Data Source

After preparing the SAP Application Server URL, User, Password, Instance No, and Client ID, click Server – Manage Sources – Add to create a data source.

Fill in the Name and other connection information.

Test the connection, and after the message Connect successful appears, save it.

Step 2. Create Destination

Prepare the AWS Redshift ODBC endpoint, access credentials, and install the ODBC driver.

In the AWS Redshift console, download and install the Redshift ODBC Driver.

Record the endpoint address of the Redshift cluster, then go to the cluster to create a database access account and authorization.

In Universal Designer, click Server – Manage Destinations – Add to create a Destination.

• Name: destination name
• Type: Redshift
• Endpoint: AWS Redshift cluster endpoint address
• Port: Redshift cluster access port
• User name, Password: Redshift database credentials
• Database: target database

After filling it out, run Test connection. If successful, save it.

Step 3. Data Extraction

Prepare the already created Source and Destination.

Click New, select the created source in Source, fill in the extraction Name, and choose Table.

Click Add to find the table to be extracted.

Select the fields to be extracted. After verification, save it. Depending on actual needs, you can configure field Aggregation, Join tables, Where filter conditions, and Having clauses, etc.

Next, modify the destination. By default, the newly created extraction destination is set to http-csv file. Right-click the extraction, choose Destination Settings, and change the Destination to the pre-created one.

In this window, you can configure S3 target table name, folder, compression method, etc.

Finally, run the extraction. Right-click the extraction and choose Run, or directly click Run in the main window. This will run the process and extract the data table from SAP into AWS S3.

In this way, Theobald Xtract Universal extracts SAP data into Amazon S3. We hope these steps help you easily access SAP system data!

The post Theobald Xtract Universal Case Series #03: Extracting Table Data from SAP BW to Amazon Redshift first appeared on DKM Ecosystem.

We tried extracting SAP data into Amazon S3, and the whole process was very convenient. Here, we will share the specific steps to help users quickly access SAP data!

Step 1. Create Data Source

First, click Server – Manage Sources – Add to create a data source.

Enter the SAP S4/HANA access information.

Finally, once the connection test succeeds, just save it.

Step 2. Create Destination

At this step, you need to have the Amazon S3 access account Access Key ID and Secret Key prepared in advance.

First, click Server – Manage Destinations – Add to create a destination.

Fill in the Name, select S3 AWS from the Type dropdown menu, and enter the access information. For Connection, choose Use user credentials.

Once the test connection succeeds, save it.

Step 3. Data Extraction

After completing the first two steps, you can create a data extraction.

First, click New, select the created data source in Source, enter an extraction Name, and choose Table.

Select the data you need to extract, use the Load live preview function to preview the data, and once confirmed, click OK to save.

Right-click the newly created extraction in the list, choose Destination Settings, and change it to Amazon S3.

Run the data extraction and check the results.

In this way, Theobald Xtract Universal extracts SAP data into Amazon S3. We hope these steps help you easily access SAP system data!

The post Theobald Xtract Universal Case Series #02: Extracting BW Cube from SAP S/4HANA to Amazon S3 first appeared on DKM Ecosystem.

Here, let’s first share the quick connection method for Theobald Xtract Universal!

Step 1.

Launch the Xtract Universal software. The trial version does not require user credentials; simply click “connect” to log in.

Step 2.

After entering the main interface, click “New” to create a new job.

Step 3.

In the pop-up dialog, you can choose the export type and name the job. The first thing to do is to define the data source: click “+” on the interface to create a new data source.

Step 4.

The data source definition interface is shown below. Here you need to use the SAP username, password, server address, and instance number to connect.

Step 5.

After creating the data source, go back to the job creation window. Select the created data source in Source, name the job, and select the type of data to be exported. After finishing, click “OK”.

Step 6.

In the pop-up dialog, you can select the data entity to be exported. Click “+Add” to get the list of entities. Select the desired data entity from the list, then click “OK”.

Step 7.

After refreshing the data, you can see the related fields and comments of the selected entity in the Fields box. You can check or uncheck boxes to select and trim required fields, and also perform joins, filters, and data aggregations. After processing the data, click “OK”.

Step 8.

Return to the main interface, select the newly created job, and click “Destination” to configure the target destination.

Step 9.

In the pop-up dialog, click “…” to see destination options and settings.

Step 10.

In the Type dropdown, you can select the target destination type (for example, MySQL database). You will need the target database username, password, and address for the connection. After filling in the database parameters and successfully testing the connection, click “OK”.

Step 11.

In the pop-up dialog, under Preparation, you can choose the way to process the data (options include Create If Not Exists, Drop & Create, Custom SQL, None, etc.). You can also configure initialization and row processing functions. After finishing, click “OK”.

Step 12.

Then, in the main interface, click “Run” to see the execution of the created job.

Step 13.

Finally, verify the data at the destination to ensure correctness.
Note: In Preparation, I chose the Create If Not Exists option. This method creates a new table in the target database to store the source data, and the table name is the same as the job name.

With this, the connection to Theobald Xtract Universal is complete. We hope these steps help you easily access SAP system data!

The post Theobald Xtract Universal Case Series #01: Connecting to SAP in Minutes with Xtract Universal first appeared on DKM Ecosystem.

In the field of cloud data management, Amazon Web Services (AWS) offers a variety of storage and analytics solutions. Among them, Amazon Redshift and Amazon S3 are undoubtedly two of the most favored services by enterprises.

However, for organizations aiming to extract and transfer SAP data, understanding the differences between these two services is crucial.

This article uses Theobald’s SAP integration tools as an example to explore how Xtract Universal integrates with both platforms, helping enterprises choose the best-fit target based on their needs.

How Does Xtract Universal Extract SAP Data?

As a versatile tool, Xtract Universal supports the following ten extraction types, helping enterprises meet diverse SAP data extraction requirements. As shown below, you can use these components to extract data from SAP systems to Amazon targets.

BAPI: Access BAPI and RFC function modules.

BW Cube: Extract data from SAP BW InfoCubes and BEx queries.

BW Hierarchy: Extract hierarchical structures from SAP BW/BI systems.

DeltaQ: Extract data sources (OLTP) and extractors from ERP and ECC systems.

ODP: Extract data via the Operational Data Provisioning (ODP) framework, supporting CDS views, HANA views, BW/4HANA objects, BW extractors, and SLT servers.

Open Hub Services (OHS): Extract InfoSpokes and OHS targets.

Query: Extract ERP queries (SQ01).

Report: Extract ABAP reports (T-Codes).

Table: Extract data from SAP tables and views, supporting joins of multiple SAP-side tables.

TableCDC: Extract change data from SAP tables.

With these powerful components, Xtract Universal enables efficient SAP data integration into Amazon Redshift and S3, leveraging the strengths of both platforms. Redshift provides high-performance analytics and fast querying capabilities, while S3 offers scalable and flexible storage for various data types.

Whether for real-time analytics or long-term storage and retrieval, this combination maximizes the value of SAP data—empowering enterprises to handle needs ranging from live insights to large-scale data management, all while maintaining the required flexibility and performance to stay competitive in a data-driven environment.

Xtract Universal + Amazon Redshift = ?

Amazon Redshift is a fully managed, high-performance cloud data warehouse designed for large-scale analytics. Leveraging columnar storage and Massively Parallel Processing (MPP), Redshift performs complex queries on structured data with high speed.

Diagram: Amazon Redshift analyzes structured and semi-structured data across data warehouses, operational databases, and data lakes using SQL, AWS-designed hardware, and machine learning to deliver optimal cost-performance at any scale.

Xtract Universal works with Amazon Redshift in the following ways during SAP data extraction:

› Structured Data Loading

👉 Xtract components simplify the process of loading structured and multidimensional SAP data into Redshift, supporting large dataset analytics and fast query performance.
👉 SAP data can be efficiently extracted into Redshift to support detailed operational reporting and centralized data warehousing, including financial records, sales data from InfoCubes, and enterprise hierarchies.
👉 Redshift’s columnar storage and high performance enhance deep analysis and complex querying of SAP data.

› BI Tool Integration

Amazon Redshift integrates seamlessly with BI tools, supporting data visualization and reporting immediately after data transfer—ideal for real-time analytics and dashboard displays.

› Data Transformation

Before SAP data enters Redshift, Xtract components ensure proper mapping of SAP ABAP data types to Redshift data types.

› Batch and Real-Time Loading

Redshift supports batch and near real-time loading, and Xtract Universal improves the efficiency of this data ingestion process.

Amazon Redshift is ideal for:

High-performance analytics: When large volumes of structured data require fast query response.

Operational reporting: Summarized and detailed reports based on SAP operational data.

Data warehousing: Centralized storage and analysis of both SAP and non-SAP data.

To learn more about how Amazon Redshift transforms and manages SAP data, see “Theobald Xtract Universal Use Case: Extracting Tabular Data from SAP BW to Amazon Redshift.”

Xtract Universal + Amazon S3 = ?

Amazon S3 is a scalable object storage service optimized for massive data storage. It excels in durability, availability, and cost-effectiveness—especially for unstructured and semi-structured data.

Diagram: Illustrates how data moves into Amazon S3, how it’s managed there, and how it can be analyzed using other AWS services—from left to right across three phases.

Xtract Universal works with Amazon S3 in the following ways during SAP data extraction:

› Flexible Data Storage

👉 Xtract components transfer large volumes of data from SAP systems to S3, supporting the creation of centralized data lakes for long-term retention and future processing.
👉 S3 can store various data types—from hierarchical structures and custom data objects to multidimensional BW data and delta-captured records—meeting diverse modeling needs.
👉 S3 is scalable and cost-effective, ideal for managing large SAP datasets for batch processing or on-demand analysis.

› Cost-Effective Storage

For data not requiring low-latency access, S3 offers cost-effective storage solutions—ideal for backups, logs, or infrequently accessed historical data.

› Integration and Data Movement

S3 is an ideal staging area in ETL (Extract, Transform, Load) workflows. Xtract Universal can stage data in S3, then use AWS services like Glue or Lambda for further transformation and migration to other targets, including Redshift.

Amazon S3 is ideal for:

Big data storage: Storing massive SAP datasets for batch processing or big data analytics.

Data archiving: Long-term storage for SAP reports, logs, and historical data.

ETL staging area: Intermediate storage before moving and transforming data to other databases or warehouses.

Differences in Data Handling Between Redshift and S3

When choosing a target platform for SAP data storage, understanding the differences between Redshift and S3 is essential, particularly in terms of data structure, accessibility, cost, and performance.

› Data Structure and Accessibility

Amazon Redshift is optimized for structured data and ideal for immediate analysis after loading.
Amazon S3 supports both structured and unstructured data but is not designed for direct querying—better suited as a repository for raw data.

› Cost and Performance

Amazon Redshift is generally more expensive due to its high-performance capabilities, ideal for performance-critical environments.
Amazon S3 offers cost-effective storage for data accessed infrequently or used for backups and archiving.

Conclusion: Try Xtract Universal for Free

Regardless of the target environment, Theobald Xtract Universal enables seamless SAP data integration—empowering enterprises to achieve more agile and effective SAP data management and analytics.

If you’re looking for a simple, user-friendly, secure, and cost-effective SAP integration solution, you can apply for a free trial of Xtract Universal or contact us for more information!

The post Use Xtract Universal to efficiently migrate SAP data to Amazon S3 or Redshift. first appeared on DKM Ecosystem.