TimeXtender Release Highlights: Xtend26 Edition

The annual TimeXtender Xtend event recently took place at Circuit Zandvoort: besides a celebration of 20 years of TimeXtender, there was of course plenty of room for TimeXtender's latest features and development direction. Alongside Xtend, new releases of TDI and TDP were also published. Below are the most striking new developments.

Data source providers

The most important improvement here is the addition of streaming support for large file-based data sources such as CSV, Parquet and XML/JSON. Previously, TimeXtender Ingest Services had to load the entire source file into memory and convert it to parquet before the data was sent to Ingest storage. This required quite a lot of memory on the TIS VM. A common workaround was to split files into chunks externally, or to limit ingestion to the bare minimum. With the streaming solution, fewer resources are needed and data can start flowing sooner. The speed gain is quite dramatic for large files: with a 4GB CSV file we saw an improvement from 7 hours for a load to 25 minutes (with specific infrastructure and scale), with much lower RAM and CPU usage. The Parquet and XML/JSON providers now also support incremental load in TDI.

There are also further improvements and fixes for many connectors; you can find the details here: Data Source Providers r. 2026-05-13 | Community

TDI Preview Features

As of the TDI 7361.1 release there are a number of Public Preview features: these can be used as normal, but work is still ongoing on stability improvements. In addition to Fabric Lakehouse and Fabric SQL for Prepare storage, you can now also use Fabric Warehouse as Prepare storage in Simple Mode. If you plan to switch to this Fabric variant, you could already test it in a Prepare-to-Prepare setup. This does require a Lakehouse Ingest, and a Lakehouse Prepare for transformations is then recommended.

Fabric Lakehouse now supports Materialized Views, so you can use them with Table Inserts. This avoids the drawbacks of the SQL Analytics endpoint that comes with regular views.

For Snowflake we now support Snowflake on AWS: you are no longer limited to the Azure variant only. You can also now define table-level security in your Snowflake Prepare using the same functionality we already know from SQL Server. However, because Snowflake does not implement DENY the way SQL Server does, you can only define positive authorizations.

The MCP Server has now reached version 2.0. This means support for https connections, Snowflake, Fabric, and a direct cloud connection that lets you expose your MCP Server to AI tools hosted elsewhere without having to set up firewalling. You can make multiple models available through a single MCP server instead of the limitations that existed before.

For Ingest metadata, you can now define data type overrides directly from the edit screen in the Metadata Manager, instead of constantly having to switch back and forth between the Metadata Manager and the Data Type Override menu. Import/export capabilities have also been added, which make it much faster to set up similar sources.

There are also many smaller improvements and fixes; see the full release notes here: TimeXtender Data Integration 7361.1 (Public Preview) | Community

TimeXtender Data Platform 26.2

During Xtend there was a showcase of TimeXtender Data Platform: the main starting point for TDI / Orchestration / Quality. Instead of separate portals for all components, this will soon be the central way to manage all aspects of TimeXtender. From 26.2 you will see a new layout and new features, which will be rolled out gradually over the coming period. This also comes with an API that lets you manage API keys and orchestration programmatically. You can now control and configure Data Quality, Data Enrichment and Orchestration in the browser to give your data the quality needed for applying AI. You can also do the latter from TDP in the Public Preview of Xpilot Analytics. Xpilot Analytics uses your MCP Server to retrieve insights from your data through a dialogue. The entire chain of TimeXtender solutions thus comes together to enrich your data into a set that is ready for AI.

See the full list of changes here: TimeXtender Data Platform 26.2 | Community

All in all, there are many improvements to explore! This summer we will visit a lot of customers on our TimeXtender Summer Tour to demonstrate TimeXtender Data Platform in full breadth, and we will also host an online demo of TimeXtender if your interest has been piqued.