VirtualZ
PropelZ
Accessing Mainframe Data from Databricks
Seamlessly integrate mainframe data into Databricks for powerful insights and real-time processing.
Seamless Integration with Databricks
Designed for optimal compatibility with Databricks, allowing organizations to efficiently connect their mainframe data with Databricks’ robust analytics and machine learning capabilities.
Automated Data Pipeline
Automate the extraction, transformation, and loading (ETL) of mainframe data into Databricks, removing manual tasks and ensuring that data is consistently updated and ready for analysis.
Secure Data Transfer
Secure and encrypted transfer of mainframe data to Databricks, protecting sensitive information throughout the data movement process and maintaining compliance with data governance policies.
Data Optimization for Analytics
Optimze mainframe data for efficient storage and processing within Databricks, enhancing query performance and minimizing storage costs, which is crucial for large-scale analytics operations.
Scalable Storage and Processing
By leveraging Databricks’ cloud-native architecture, store and process large volumes of mainframe data without the constraints of traditional infrastructure, enabling flexible and scalable analytics.
Ready to integrate mainframe data into Databricks for scalable, real-time analytics?
Cost Savings
Transitioning mainframe data to Databricks can significantly reduce on-premises storage costs, taking advantage of Databricks’ pay-as-you-go model for cloud services.
Simplified Data Management
The integration of mainframe data into Databricks simplifies data management, providing a single platform for analytics while enhancing ease of access and data governance.
Accelerated Insights
With real-time access to mainframe data directly in Databricks, businesses can perform faster analytics and reporting, driving timely decision-making.
Increased Flexibility
Leverage Databricks’ powerful data processing capabilities alongside existing mainframe systems, enabling a hybrid approach to data architecture.
Enhanced Data Availability
By ensuring that mainframe data is readily accessible within the Databricks environment, organizations can improve operational efficiency and enable data-driven strategies across their business operations.