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Ilum

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23 reviews
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4.9
Serving customers since
2019
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ILUM

23 reviews

Ilum is a free data lakehouse platform designed for scalability, flexibility, and simplicity.

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Ilum

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Ilum is a comprehensive data lakehouse platform designed to streamline the management and monitoring of Apache Spark clusters across cloud, on-premise, and hybrid environments. It integrates seamlessly with tools like Jupyter, Apache Airflow, and MLflow, providing a unified solution for data scientists, cloud engineers, data analysts, IT administrators, and machine learning engineers. Ilum supports open table formats such as Delta Lake, Apache Iceberg, and Apache Hudi, ensuring flexibility and avoiding vendor lock-in. Its Kubernetes-native architecture offers scalability, high availability, and dynamic resource management, making it a modern alternative to traditional data platforms. Key Features and Functionality: - Unified Multi-Cluster Management: Manage multiple Spark clusters across various environments through a single platform. - Interactive Spark Sessions: Engage with Spark jobs via a REST API and user-friendly web interface, eliminating the need for command-line interactions. - Integration with Data Tools: Seamlessly integrates with Jupyter, Apache Airflow, MLflow, and business intelligence tools like Tableau and Power BI. - Support for Open Table Formats: Works with Delta Lake, Apache Iceberg, and Apache Hudi, ensuring ACID compliance and efficient data storage. - Kubernetes and Hadoop Yarn Integration: Facilitates easy deployment and management of Spark jobs on Kubernetes and integrates with Apache Hadoop Yarn. - Scalability and High Availability: Offers horizontal scalability and dynamic resource scaling to handle workloads of any size. - Data Governance and Security: Provides data lineage tracking, role-based access control, and integration with Apache Ranger for enhanced security. Primary Value and Problem Solved: Ilum addresses the challenges of managing and monitoring Apache Spark clusters by providing a unified, scalable, and flexible platform. It simplifies operations across diverse environments, supports open table formats to prevent vendor lock-in, and integrates with a wide range of data tools. By offering interactive sessions, multi-cluster management, and robust data governance, Ilum enhances operational efficiency, accelerates data processing tasks, and empowers organizations to build and deploy data-driven applications with ease.

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Ilum Reviews

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Verified User in Airlines/Aviation
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Verified User in Airlines/Aviation
08/07/2025
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Verified Current User
Review source: Organic

Team-Menager

|ILUM
It provided us with a dependable structure for handling intricate engineering datasets throughout the entire RF development workflow. We work with diverse sources like simulation outputs, lab results, PCB schematics, and mechanical CAD files — each originating from separate systems, teams, and testing setups. Previously, this information was scattered and disconnected. Now, it’s unified, version-controlled, easy to access, and fully traceable. Thanks to it, we moved away from thinking of data as static assets and began treating it as a dynamic and trustworthy foundation — whether we're integrating simulation data into verification pipelines, analyzing long-term test results, or preparing curated inputs for future AI applications. It integrates seamlessly with our current tooling and brings transparency and consistency across all product stages.
JJ
Jens J.
08/07/2025
Validated Reviewer
Verified Current User
Review source: Organic

Ilum connects the dots between data and real AI

|ILUM
Ilum helped our company clean up the data mess that used to block serious AI work. Instead of scattered files, multiple storage layers, and unclear schemas, we finally had one consistent layer where all the data lived, structured, unstructured, didn’t matter. It was versioned, searchable, trackable, and easy to work with. No more guessing which file was the right one. That foundation made it possible to build high-quality, trustworthy datasets. From there, everything clicked. We could train models without wrangling chaos first. Jupyter and MLflow worked out of the box. Pipelines actually ran cleanly. Ilum didn’t just help with AI, it made AI feasible in our environment. We’re using it daily now. Spark jobs, scheduled pipelines, notebooks, data exploration, metadata tracking, monitoring, all of it in one place. It replaced a patchwork of tools and made the whole platform easier to manage. Setup was fast. We didn’t need outside consultants. It worked with our existing stack and auth, and the UI is simple enough that non-engineers on the team can still explore data and run queries without friction. Integration was surprisingly smooth. Ilum fit into our stack without forcing any major rewrites. We deployed it on Kubernetes, wired it to our existing GitLab auth, connected it to both cloud object storage and on-prem HDFS, and it just worked. Support has also been solid. Helpful responses, quick turnaround, and not just generic copy-paste replies—actual solutions that fixed problems. What I like most is that Ilum gives you a lot of power without feeling heavy. The features are deep, but they make sense. You don’t have to rebuild your world to fit it in. It plays well with what you already have and gives you structure without locking you in.
BC
Bartłomiej C.
08/06/2025
Validated Reviewer
Verified Current User
Review source: Organic

Ilum mvp review

|ILUM
Almost out of box installation (docker with helm) and cost optimization when switching to their dynamic sessions. I had one problem when creating MVP for internal use and even tho I didn't paid for anything and contacted with Ilum developers they have helped me to solve my problem. My BA and data team was really happy that they had like jupyter or other features coming together with the product and it was very easy to use existing k8s cluster for integration.

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Santa Fe, US

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What is Ilum?

Ilum - Free Data Lakehouse

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Year Founded
2019
Website
ilum.cloud