Build Your Modern Data Estate 10X Faster
Let us show you how…
Easy Data Integration
Connect to over 200 database types and cloud data sources through our pre-built data connectors to integrate data from multiple sources. No need to develop, test, debug and maintain critical data source connections. You can configure each connector to extract exactly the data you need. Or build custom connectors for your proprietary sources.
Automated Code Generation
Expedite development with automated code-generation, freeing data engineers to focus on data quality and business requirements. Eliminating the writing, reviewing and debugging of countless lines of SQL code. TimeXtender generates T-SQL code for data cleansing, transformation, validation, unions and joins using project meta-data and maintains that code for you.
Automate and Optimize Data Loading
TimeXtender manages all the scripts it generates for data integration, loading, transformation, preparation and modeling. It optimizes data loading by learning from past executions – eliminating manually setting up and maintaining object dependencies and manually optimizing orchestration tasks. It also optimizes execution with parallel processing over multiple threads.
Manage and Transfer Data Between Multiple Environments
TimeXtender eliminates manually translating work to provide the same data to different endpoints. This means we can maintain your Development, Test and Production systems and move work between them – even if they are on different data platforms. Meaning you can develop via SQL Server on-premises, test in Azure SQL Database and deploy to production on Azure SQL MI or SQL Data Warehouse.
How is TimeXtender 10X Faster for Building Your Data Estate?
Eliminate writing, reviewing and debugging countless lines of SQL code
Eliminate generating huge and complex ETL flows for simple use cases
Eliminate countless hours trying to trace complex ETL to identify problem areas
Eliminate learning a large set of tools for build components of the data estate
Eliminate constant performance analysis and adjusting ETL flows to ensure efficient executions
Eliminate writing documentation for flows and transformations
Eliminate maintaining old versions of project code
Eliminate pain of rolling back to a previous version
Eliminate translating work to provide the same data to different endpoints