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ML platforms · November 2026 Edition

Databricks Mosaic AI vs Dataiku

Three of fourteen models named Databricks Mosaic AI first on the direct prompt; four named Dataiku. Databricks Mosaic AI was named by fourteen of the fourteen models and Dataiku by eleven and Databricks Mosaic AI carries 53 labels and Dataiku 23, so the shares are not directly comparable.

Databricks Mosaic AI

accepted challenger

Named in one category this edition.

Dataiku

accepted challenger

Named in two categories this edition.

First-choice share24%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate9%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#3A position in a field of 15; printed, not drawn.
Labels5323A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Databricks Mosaic AI reading right to left. Rank and label count are printed, not drawn.Azure Machine Learning was named alongside these two in twelve of the fourteen direct answers. Databricks Mosaic AI vs Azure Machine Learning · Databricks Mosaic AI vs Amazon SageMaker · Databricks Mosaic AI vs MLflow

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the ML platforms page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Databricks Mosaic AIFirst choices, of fourteen modelsDataiku
Direct342 against Databricks Mosaic AI
Paraphrase100
Comparative00
Budget-constrained011 against Databricks Mosaic AI
Scale-constrained10
Negative002 against Databricks Mosaic AI
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Databricks Mosaic AI and Dataiku were named in the same answer sixty-one times, of the 151 answers naming Databricks Mosaic AI and the 83 naming Dataiku. In those answers Dataiku took the first choice eight times and Databricks Mosaic AI seventeen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Databricks Mosaic AI and Dataiku stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Databricks Mosaic AI Dataiku first choice named as an alternative argued againstblank: not namedEach cell is one answer, Databricks Mosaic AI on the left and Dataiku on the right.

The direct prompt

The plain question, one answer per model, grouped by where Databricks Mosaic AI and Dataiku stood in it.

Databricks Mosaic AI first, Dataiku an alternative

3 of 14 modelsDataiku was named in the answer but not as the choice, or not at all.
GPT-5.4 miniDatabricks Mosaic AI alternatives: Amazon SageMaker, Snowflake Cortex AI
MiniMax M2.5Databricks Mosaic AI, Snowflake Cortex AI alternatives: Amazon SageMaker, Azure Machine Learning, Dataiku, Domino Data Lab, Google Vertex AI
GPT-6 LunaDatabricks Mosaic AI alternatives: Azure Machine Learning, Gemini Enterprise Agent Platform, Snowflake Cortex AI

Dataiku first, Databricks Mosaic AI an alternative

4 of 14 modelsDatabricks Mosaic AI was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashDataiku alternatives: Amazon SageMaker, DataRobot, Databricks Mosaic AI, GCP Vertex AI, Google BigQuery ML, Snowflake Cortex AI
Grok 4.20Dataiku alternatives: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Google Vertex AI
Kimi K2Azure Machine Learning, Dataiku alternatives: Amazon SageMaker
Muse Glimmer 30BAzure Machine Learning, Dataiku alternatives: Amazon SageMaker, Databricks Mosaic AI, Google Vertex AI, Snowflake Cortex AI

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5no first choice alternatives: Amazon SageMaker, Azure Machine Learning, Clearly.ai, DataRobot, Databricks Mosaic AI, Google Vertex AI, H2O AutoML
Perplexity SonarAzure Machine Learning alternatives: Amazon SageMaker, Databricks Mosaic AI, Dataiku
Mistral SmallAzure Machine Learning, Snowflake Cortex AI alternatives: DataRobot, Databricks Mosaic AI, Google Vertex AI
DeepSeek V4 FlashAzure Machine Learning alternatives: Amazon SageMaker, DataRobot, Databricks Mosaic AI, Snowflake Cortex AI
Qwen 3.7 FlashDataRobot alternatives: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI
GLM 4.7 FlashXAmazon SageMaker, Azure Machine Learning alternatives: Databricks Mosaic AI, Google Vertex AI

Neither was named

1 of 14 modelsThe answer made no first choice from these two in this category.
Llama 4 MaverickAzure Machine Learning alternatives: DataRobot, Google Vertex AI, IBM watsonx.ai, Snowflake Cortex AI

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Dataiku leads by two points.
Dataiku2%#11 of 15
Databricks Mosaic AI0%#14 of 15
The full small business standing →
Mid-marketThe figures above
The order flips: Databricks Mosaic AI leads at mid-market.
Databricks Mosaic AI24%#1 of 15
Dataiku9%#3 of 15
The full mid-market standing →
Enterprise
Databricks Mosaic AI leads by forty-three points.
Databricks Mosaic AI49%#1 of 11
Dataiku6%#4 of 11
The full enterprise standing →

What the models said about Databricks Mosaic AI

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“Avoid heavy enterprise tools like Databricks or full SageMaker unless you have specific needs” Grok 4.20 · budget prompt · hard negative
“Why to be Cautious: These platforms often have steep learning curves and high entry costs.” Qwen 3.7 Flash · negative prompt · soft negative
“without the complexity and cost of full enterprise solutions like Databricks or Palantir” Kimi K2 · direct prompt · soft negative
“Leaders: Databricks (Unity Catalog, MLflow)... the "big three" cloud-native platforms (AWS, Azure, GCP) or Databricks are often the safest bets” MiniMax M2.5 · scale prompt · first choice
“choose Databricks MLflow/Mosaic AI or a pure MLflow stack if you prioritize vendor neutrality, data-lake integration and lower long-term cost” Muse Glimmer 30B · paraphrase prompt · first choice
“Databricks (MLflow / Mosaic AI) - Best for organizations unifying data engineering and machine learning on a single lakehouse.” Llama 4 Maverick · paraphrase prompt · first choice

What the models said about Dataiku

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Best for limited data-science headcount + governance: Dataiku. End-to-end, no/low/full-code, strong governance/monitoring and vendor-agnostic.” Muse Glimmer 30B · direct prompt · first choice
“starting with KNIME or Dataiku's free tier allows you to prove value without spending money” Qwen 3.7 Flash · budget prompt · first choice
“Dataiku and Azure Machine Learning are frequently recommended as the sweet spot” Kimi K2 · direct prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.