Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Answered
We Are Currently Product-Hunting For Our Mlops Infrastructure And Clearml, Kedro, Mlrun Are On Our Short List. How Does Clearml Compare To Mlrun? One Big Difference Seems To Be That Mlrun Has A Feature Store Integrated. What Are Advantages/Disadvantages O

We are currently product-hunting for our MLOps infrastructure and ClearML, Kedro, MLRun are on our short list. How does ClearML compare to MLRun? One big difference seems to be that MLRun has a feature store integrated. What are advantages/disadvantages of each, compared to each other?

  
  
Posted 2 years ago
Votes Newest

Answers 8


GrittyStarfish67 : Thanks! But how are those for ClearML vs MLRun? Granted, ClearML has a ~5 times more github stars than MLRun, but besides that: Both are from mid 2019 according to releases on git. I have not been in their slack and I know nothing about community adoption. (Btw, Kedro has twice as many stars than ClearML - even if it has far fewer feature, those that it does have, seem pretty well done.)

  
  
Posted 2 years ago

Hi VivaciousBadger56
Basically you can think of MLRun as "amazon lambda service without amazon". It is designed to run a "function" in scale on multiple nodes.
ClearML on the other hand is an MLOps platform. It does the experiment tracking, it orchestrates Task (think jobs), it does data management and lastly we recently released the serving. These are two different use cases.
Am I making sense here?

  
  
Posted 2 years ago

AgitatedDove14 : Not sure: They also have the feature store (data management), as mentioned, which is pretty MLOps-y 🙂 . Also, they do have workflows ( https://docs.mlrun.org/en/latest/concepts/multi-stage-workflows.html ) and artifacts/model management ( https://docs.mlrun.org/en/latest/store/artifacts.html ) and serving ( https://docs.mlrun.org/en/latest/serving/serving-graph.html ).

  
  
Posted 2 years ago

Not sure: They also have the feature store (data management), as mentioned, which is pretty MLOps-y

.

Right, sorry, I was thinking about "Nuclio", my bad.

How would you compare those to ClearML?

At least based on the documentation and git state I would say this is very early stages. In terms of features they "tick all the boxes", but I'll be a bit skeptic on the ability to scale and support these features.

Taking a look at the screenshots from the docs, it also seems someone really tried to copy the ClearML experience, which tells you something about the product:
https://docs.mlrun.org/en/latest/_images/pcp.png

  
  
Posted 2 years ago

VivaciousBadger56 You’re basically answering yourself 😉 so kedro = lean feature strong community, ClearML many features small (growing) community and mlrun has a good name

  
  
Posted 2 years ago

Hi, just chiming in with a lesson learnt on my subreddit r/mlops - when shortlisting open-source MLOps infra, the bundled features are less important KPIs than stability and longevity markers:
community adoption active slack channel good documentation clear monetization scheme (how much does it cost if you decide to go SaaS instead of paying for own infra) - even if you never intend to go SaaS, it helps to understand if the OSS is actually “freemium” or not.
Hope that helps!

  
  
Posted 2 years ago

GrittyStarfish67 : In terms of "has a good name" you literally mean the name or do you mean, they have a good reputation 😄 ?

  
  
Posted 2 years ago

How would you compare those to ClearML?

  
  
Posted 2 years ago