Improved SQL Editor with Selective Query Execution! 🎯

We’ve upgraded the Ilum SQL Editor with a powerful new feature: select and run specific queries directly from a single view—no need to execute the entire notebook or clean up your workspace first.

Key Enhancements:
🧩 Query Picker – Quickly choose which query to execute from a list of all defined queries in your notebook.
🎯 Focused Execution – Run only the SQL block you need, saving time and avoiding unnecessary data scans.
🧭 Better Navigation – Easily jump between queries and manage your workflow more efficiently.
💡 Cleaner Debugging – Isolate and test specific parts of your SQL logic without affecting the rest of the notebook.

This improvement brings more control and flexibility to your data exploration and debugging workflows. Whether you're refining a single query or testing logic step-by-step, Ilum makes it faster and easier.
Give it a try and streamline your SQL journey! 🚀

improved sql ilum view

Enhanced SQL UI with Notebook-Style Execution

We've upgraded Ilum’s SQL Editor to support notebook-style operations, making it easier than ever to explore, query, and analyze big data at scale. Starting now, you can write & execute SQL in structured cells, just like in Jupyter Notebook, instead of running your Apache Spark SQL queries one by one. This enables you to run SQL or SQLite queries similar to a Jupyter Notebook. So instead of running Apache Spark SQL queries one by one, you can write and execute SQL in structured cells. 

Key Improvements: 
- Notebook-style SQL execution – Run and organize queries in cells for a more interactive SQL analytics experience. 
- Persistent query history – Save and revisit SQL jobs for improved workflow management. 
- Multi-cell execution – Execute individual cells or entire SQL notebooks for fast, scalable data exploration. 
- Integrated with BI & Data Platforms – Query data stored in cloud data lakes, data warehouses, and on-prem storage via JDBC integration. 

With this update, it is easier to query SQL inside Ilum and manage data lakehouse, business intelligence and big data analysis.  Check it out today and meet the better way to manage your structured and semi-structured data! 🚀

ilum-improved-sql.png 180.53 KB


Version 6.1.1

  1. Added replica count to Helm charts.
  2. Added node affinities for architectures to helm charts
  3. Added the ability to browse attached cluster storages
  4. Fixed a bug with Kafka consumer configuration

Version 6.0.0

Version 5.2.0


Version 5.1.0


Version 5.0.2

  • Enhanced user interface with subtle refinements for an improved user experience.
  • Extended ilum-job-api to maintain seamless backward compatibility with Java 8, ensuring support for legacy systems.

Version 5.0.1

  • Introduced versatile, multi-platform Docker images for ilum-core, expanding compatibility and usability across various systems.
  • Revitalized Bitnami Helm repository with essential updates to dependencies, ensuring seamless access and functionality.
  • Implemented subtle user interface enhancements for a more polished and user-friendly experience.

Powered by FeedBear