Over 200 data teams already unlocking insights with Ilum's
Managed Data Lakehouse for Any Deployment
Unlock the flexibility of Ilum’s free managed data lakehouse platform, designed to be deployed across on-premise, cloud, or hybrid environments. Our modern data lakehouse architecture combines the flexibility of data lakes with the speed of warehouses – Ilum gives you both, offering a complete Spark on Kubernetes solution without the cost.
The Power to Customize Your Data Platform
Ilum empowers you to choose the tools that fit your workflow best, whether it’s Delta Lake, Apache Iceberg, or Apache Hudi.
You’re not locked into a single BI tool or Notebook. Connect with PowerBI, Tableau, or use our built-in modules like Superset.
Whether you want to integrate with Apache Airflow for orchestration, run exploratory analysis in Jupyter, or leverage ML tools like MLflow for your machine learning pipelines, Ilum supports it all.
With Ilum, you maintain full control to build a data ecosystem that perfectly matches your needs.
Explore our EcosystemKubernetes Native
Leverage the scalability and robustness of Kubernetes without the hassle of manual configuration.
Flexible Storage
Connect to build-in S3 based interface or use: Amazon S3, Azure Storage, Google Cloud Storage, HDFS.
Anywhere
Deploy Ilum anywhere — be it on the cloud, on-premise, or a hybrid environment, giving you the ultimate flexibility in deployment.
Managed Spark Cluster on Kubernetes
Tired of the complexity of Hadoop or Cloudera? Ilum delivers the power of Apache Spark and Airflow without the headache, offering a seamless cloud-native data platform alternative.
Managing a Spark Cluster can be challenging, but Ilum makes it straightforward. We handle the hard part of Kubernetes Spark operator management, allowing you to focus on extracting insights from your data.
With Kubernetes at its core, Ilum automates spark cluster provisioning, scales resources dynamically based on workload demands, and ensures high availability for your big data workloads.
Ilum is not just a platform for managing and monitoring Apache Spark on Kubernetes. It also serves as your own fully managed Spark cluster and Data Lakehouse.

Observability at your hands
Eliminate the guesswork in debugging with Ilum’s detailed logs and metrics. Easily dive into Spark logs and performance metrics, all in one place, making it simpler to identify bottlenecks and issues that are often hard to trace in standard environments.
Debugging and Monitoring with Ilum
Ilum provides a unified environment for monitoring your Spark jobs through detailed logs and performance metrics. While traditional environments make it challenging to access logs and metrics in one place, Ilum simplifies this process, allowing developers to dive deep into Spark logs and metrics without switching between multiple tools.
By offering centralized access to key logs and real-time performance metrics, developers can quickly pinpoint bottlenecks, trace errors, and optimize Spark jobs. It provides the essential insights needed to resolve issues faster and improve cluster performance.
This streamlined approach improves productivity by keeping vital monitoring resources at your fingertips, making it easier to manage and troubleshoot your Spark environment.
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