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ETL and ELT · October 2026 Edition

Hevo Data vs dbt

Three of fourteen models named Hevo Data first on the direct prompt; zero named dbt. Hevo Data was named by eleven of the fourteen models and dbt by twelve and Hevo Data carries 29 labels and dbt 35, so the shares are not directly comparable.

Hevo Data

accepted challenger

Named in three categories this edition.

dbt

accepted challenger

Named in five categories this edition.

First-choice share15%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%3%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 18; printed, not drawn.
Labels2935A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Hevo Data reading right to left. Rank and label count are printed, not drawn.Fivetran was named alongside these two in twelve of the fourteen direct answers. Fivetran vs Hevo Data · Fivetran vs dbt · Airbyte vs Hevo Data

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 ETL and ELT page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Hevo DataFirst choices, of fourteen modelsdbt
Direct30
Paraphrase11
Comparative001 against dbt
Budget-constrained40
Scale-constrained00
Negative01
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 October 2026 Edition, Hevo Data and dbt were named in the same answer twenty-six times, of the 99 answers naming Hevo Data and the 100 naming dbt. In those answers dbt took the first choice zero times and Hevo Data five.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Hevo Data and dbt stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
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
Hevo Data dbt first choice named as an alternative argued againstblank: not namedEach cell is one answer, Hevo Data on the left and dbt on the right.

The direct prompt

The plain question, one answer per model, grouped by where Hevo Data and dbt stood in it.

Hevo Data first, dbt not the choice

3 of 14 modelsdbt was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashHevo Data alternatives: Airbyte, Fivetran
Kimi K2Hevo Data alternatives: Airbyte, Rivery, Stitch
GLM 4.7 FlashXHevo Data, Stitch alternatives: Airbyte, Fivetran

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashFivetran alternatives: Airbyte, Hevo Data, Rivery
Perplexity SonarFivetran alternatives: Airbyte, Hevo Data
Grok 4.1 FastFivetran alternatives: Airbyte, Hevo Data, Integrate.io
Qwen 3.7 FlashAirbyte alternatives: Fivetran, Hevo Data
Muse Glimmer 30BFivetran alternatives: Apache Airflow, Estuary Flow, Integrate.io, Matillion, dbt

Neither was named

6 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
GPT-5.4 miniAirbyte, Fivetran alternatives: Matillion
Mistral SmallFivetran alternatives: Airbyte, Celigo, Workato
Llama 4 MaverickFivetran alternatives: Airbyte, Databricks Lakeflow, Domo
MiniMax M2.5Integrate.io alternatives: Airbyte, Fivetran
GPT-6 LunaFivetran alternatives: Airbyte, Matillion

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
Hevo Data leads by nineteen points.
Hevo Data19%#2 of 11
dbt0%#8 of 11
The full small business standing →
Mid-marketThe figures above
Hevo Data leads by thirteen points.
Hevo Data15%#3 of 18
dbt2%#6 of 18
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Hevo Data0%#13 of 15
dbt0%#8 of 15
The full enterprise standing →

What the models said about Hevo Data

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

“Choose Hevo Data if you want a "set it and forget it" experience with clear, low monthly pricing (~$239/mo) and minimal maintenance.” Qwen 3.7 Flash · budget prompt · first choice
“The best ETL tool for a company with a limited budget is Hevo Data, which offers usage-based pricing from $239/month” Llama 4 Maverick · budget prompt · first choice
“For most mid-market B2B companies, Hevo Data strikes the best balance of cost, ease of use, and capability.” DeepSeek V4 Flash · direct prompt · first choice

What the models said about dbt

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

“dbt is usually a complement, not a full ETL replacement” GPT-6 Luna · comparative prompt · soft negative
“use modern ELT orchestrators like dbt (Data Build Tool) coupled with lightweight extractors” Gemini 3.5 Flash · negative prompt · first choice
“ELT / transformations: dbt” GPT-5.4 mini · paraphrase prompt · first choice
“Better Alternative: For most teams, a SQL-based transformation tool like dbt or a visual low-code tool is faster and cheaper to maintain.” Qwen 3.7 Flash · negative prompt · alternative
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.