Fivetran vs dbt
Eight of fourteen models named Fivetran first on the direct prompt; zero named dbt. Fivetran was named by fourteen of the fourteen models and dbt by twelve and Fivetran carries 61 labels and dbt 35, so the shares are not directly comparable.
Named in four categories this edition.
Named in five categories this edition.
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
FivetranFirst choices, of fourteen modelsdbt
Across every category in the October 2026 Edition, Fivetran and dbt were named in the same answer eighty-three times, of the 205 answers naming Fivetran and the 100 naming dbt. In those answers dbt took the first choice two times and Fivetran thirty-eight.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | | | |
Fivetran dbt first choice named as an alternative argued againstblank: not namedEach cell is one answer, Fivetran on the left and dbt on the right.The direct prompt
Fivetran first, dbt an alternative
8 of 14 modelsdbt was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
2 of 14 modelsThe answer made no first choice from these two in this category.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
Fivetran17%#3 of 11dbt0%#8 of 11Fivetran40%#1 of 18dbt2%#6 of 18What the models said about Fivetran
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“"Airbyte & Fivetran are bad products." ... That view is not consensus, but it is representative of complaints about pricing models” Muse Glimmer 30B · negative prompt · soft negative
“Fivetran has high pricing for large row volumes using the MAR pricing model, and limited real-time support” Claude Haiku 4.5 · negative prompt · soft negative
“avoid the "billing roulette" of expensive enterprise tools like Fivetran or Informatica” Gemini 3.5 Flash · budget prompt · soft negative
“Managed, low-maintenance option: Fivetran. ... Choose Fivetran + Snowflake + dbt if you want minimal engineering overhead” Muse Glimmer 30B · paraphrase prompt · first choice
“1. Fivetran: Recommended for B2B SaaS firms heavily invested in Salesforce, HubSpot, NetSuite, and Snowflake.” Llama 4 Maverick · direct prompt · first choice
“The industry standard for zero-maintenance ELT... Choose Fivetran if you have a budget, a small data team” Gemini 3.5 Flash · comparative 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
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.