It gave us a reliable backbone for managing complex engineering data across the entire RF development process. We deal with simulation results, measurement data, PCB designs, and mechanical models, all coming from different tools, teams, and test environments. Before Ilum, that data was fragmented. Now it's all in one place, versioned, accessible, and auditable.

It helped us stop treating our data as static files and start treating it as something we can trust and build on, whether that’s feeding simulation outputs into validation workflows, comparing lab measurements over time, or prepping datasets for future AI models. It fits into our existing stack without disruption and gives us clarity across the product lifecycle. Review collected by and hosted on G2.com.

Ilum isn’t always intuitive for teams coming from pure engineering or lab environments. The UI can take some getting used to, especially if you're used to local folders and simulation tool outputs. Some workflows, like automating ingestion of simulation or measurement data required a bit of custom setup on our end. That said, once it’s running, it’s solid. Review collected by and hosted on G2.com.

ILUM is one of those rare platforms that actually fits into the world you already have—not just the world some vendor wishes you had. In our team, we have a pretty complex setup: a mix of legacy on-prem clusters, a lot of workloads in the cloud, strict compliance, and plenty of security hoops. We didn’t want to tear everything down just to introduce something new.

With ILUM, that wasn’t a problem. We got it up and running on our Kubernetes cluster much faster than expected—deployment took less than two weeks from first trial to production. For example, we were able to migrate over a dozen business-critical Spark jobs from our old setup into ILUM with minimal changes to our code or pipelines. The learning curve is there, but if your team knows Spark and K8s, it’s totally manageable.

The best part is how it just slotted in with what we already use: Spark, Jupyter, our existing MinIO storage, and even our Airflow jobs. There was no endless “integration project” — it just worked. Our data scientists use the built-in Jupyter notebooks every day for prototyping and training models, and our DevOps team appreciates having everything in one place for monitoring and management.

What I personally appreciate is that ILUM lets us keep the keys. We don’t have to ask permission or wait on a vendor for every change. Costs are predictable, data stays under our roof, and when compliance asks the tough questions, we actually have answers. ILUM’s integration with our storage and existing monitoring (including Splunk) made the audit process much easier.

To be honest, ILUM has become a regular part of our daily work. We use it all the time now — submitting jobs, tracking progress, digging through results and logs. Onboarding new team members is much faster because everything is centralized. It’s made itself almost invisible, in a good way: just there, quietly doing its job, which is honestly the best you can ask for in a platform like this. Review collected by and hosted on G2.com.

If you’re expecting a totally managed, “push button and magic happens” platform, ILUM isn’t that out of the box. You do need some Kubernetes and Spark skills on the team to get the most out of it — or at least, that’s how it was for us at the start. For instance, initial setup required help from our DevOps to get advanced networking and storage permissions right. We also had some trouble with job scheduling for custom Spark jobs, but after moving to the Enterprise plan, most of those headaches disappeared.

The ILUM team really took over the heavy lifting: onboarding, tricky configurations, and even the really specific networking quirks that come with a telco environment. They basically handled the tough parts so we could focus on our work and not the plumbing.

The documentation is good, and their support has always been responsive. But with Enterprise, the level of hands-on help went way up. When we hit a snag, someone from ILUM actually joined a call, helped us debug, and stuck with us until things were sorted. That kind of support is rare these days, and it made a real difference. Review collected by and hosted on G2.com.

Very easy to use and clear, even for new users. It was simple to set up and start working, so the implementation didn’t take much time. The customer support team is helpful and quick to respond, which I really appreciate. I use ilum almost every day because it makes my work easier and keeps everything organized. It has a good number of useful features that cover what I need, and they all work together smoothly. I also like that it integrates well with other tools I already use. Review collected by and hosted on G2.com.

I’d also like to have more visual options and flexibility in customizing dashboards, but overall, it’s a really good tool. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Unclear if product will stick to their plans in roadmap. Project seems to be lead by good technical persons but with so small number of testimonials and logos they might fade in future Review collected by and hosted on G2.com.

We run Spark on Kubernetes and ILUM gave us one place to submit jobs (via Livy), watch runs, and debug without hopping between tools. The lineage view is genuinely useful—when a column rename or schema drift sneaks in, we can trace where it broke instead of guessing. Helm install was straightforward, MinIO/S3 integration just worked, and the Airflow/Jupyter handoff feels natural. It’s not flashy, but it removed a lot of DIY glue and made day-to-day ETL more predictable. We use it every day—most mornings start on the runs page to check pipelines, and ad-hoc jobs go through ILUM as a habit now. Review collected by and hosted on G2.com.

At the beginning, the deployment and DevOps bar felt high for our team—we didn’t have dedicated Kubernetes engineers, so keeping charts, probes, and infra healthy took time. After moving to the Enterprise edition, with managed components and support, this stopped being a problem: upgrades are smoother and most of the K8s plumbing is handled for us. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Ilum can be a bit challenging at first, especially for teams used to traditional engineering or lab-centered workflows. The interface isn’t immediately intuitive if you’re coming from a background where everything lives in local folders or flows directly from simulation tools. Certain tasks — like setting up automatic data ingestion for simulations or test results — needed some custom configuration on our side. Still, once everything is in place, the system performs reliably. Review collected by and hosted on G2.com.

The biggest draw for most people is that Ilum has a free plan and is open-source, which is a huge deal because it means you're not locked into a specific vendor and you save a ton on licensing fees. You can run it wherever it makes sense for you, whether that's on your own servers or in the cloud. It also plays nicely with all the tools data people already use, like Tableau and PowerBI. Capable of managing complex tech like Spark and Kubernetes. Plus, it's also very fast, which boosts performance boosts and can amount to cost savings, especially those who have switched over from older systems. Review collected by and hosted on G2.com.

On the flip side, it's good to remember that Ilum is still new. Because it's younger, it might not have all the bells and whistles or niche features that some of the platforms that have been around for a decade have. The community around it is also still building up, so you might have to dig a bit deeper for answers compared to just finding a quick fix on Stack Overflow. That said the official support team is fantastic and super quick to help, which definitely helps. Review collected by and hosted on G2.com.

What I like best about ILUM is how quickly and easily I can get Spark jobs running, no matter if I’m in the cloud or on-premise. The setup is incredibly smooth, and the platform scales effortlessly as my needs grow. I love the interactive session management—it saves me a ton of time on analytics and experimentation. The web UI is intuitive and makes controlling everything a breeze. Honestly, even after years of use, ILUM still surprises me with how reliable and flexible it is. Review collected by and hosted on G2.com.

Honestly, there’s not much to dislike about ILUM. Sometimes the UI feels a bit minimalistic, but it gets the job done. Review collected by and hosted on G2.com.

Ilum has proven to be an outstanding tool, perfectly tailored to our needs. It offers hybrid management of data lake environments—both on-premises and cloud-based. The transition from a Cloudera-based setup to an on-premises Kubernetes environment went smoothly and resulted in significant cost savings. Continuous integration with external modules keeps expanding the platform’s capabilities. Integration with Ilum through their API was very straightforward. The dashboard stands out for its ease of use and clear, intuitive interface. Review collected by and hosted on G2.com.

We’ve been working with Ilum since the very beginning – we were among their early adopters. Of course, there were some issues along the way, but their support team always resolved everything quickly and efficiently. Review collected by and hosted on G2.com.

- Hybrid deployment support

- Modular and feature-rich platform

- Ease of integration and use

- Cost savings

- The support level is honestly the best I’ve ever experienced Review collected by and hosted on G2.com.

UI could be more polished, Documentation is improving but could be better. Review collected by and hosted on G2.com.