dbt is built for Analytics engineers and data engineers building transformation layers in cloud warehouses, Data analysts comfortable with SQL seeking to apply software engineering rigor to reporting pipelines, Data platform and data infrastructure teams at mid-market and enterprise companies, BI and analytics teams standardizing metric definitions across multiple tools. Common use cases include ELT transformation: modeling and transforming raw warehouse data into analytics-ready datasets; Analytics engineering: applying software engineering best practices (CI/CD, testing, version control) to SQL; Semantic layer: standardizing metric definitions across BI tools, AI agents, and APIs.

dbt Cloud follows a tiered, seat-based model. Developer tier is free (1 seat, 3,000 model builds/month, 1 project, browser IDE, job scheduling). Starter tier is $100/user/month (up to 5 seats, 15,000 model builds/month, dbt Semantic Layer basic, dbt Catalog basic, API access). Enterprise tier offers custom pricing (up to 30 projects, 100,000 model builds/month, advanced Semantic Layer and Catalog, dbt Mesh, dbt Copilot, Canvas, Insights, cost optimization, priority support). Enterprise+ adds PrivateLink, IP restrictions, rollback, and hybrid projects at custom pricing. dbt Core remains free and open-source under Apache 2.0. Additional warehouse compute costs are incurred separately based on the customer's data platform.

What are the alternatives to dbt?

Common Data Engineering & ETL/ELT Pipelines alternatives to dbt include Fivetran, Airbyte, Integrate.io, Matillion, Dagster. See the full comparison hub at /verticals/data-engineering-and-etl-elt-pipelines/compare.

What do users praise about dbt?

Users frequently praise: SQL-first developer experience and clean project structure; Built-in testing and data quality framework; Auto-generated documentation and interactive DAG lineage; Encourages software engineering best practices (version control, CI/CD); Thriving open-source community and documentation; Modular model architecture for managing complex transformations; Deep integration with Snowflake, BigQuery, and Databricks; Significant warehouse cost savings via stateful/incremental orchestration.

What are common complaints about dbt?

Frequently cited limitations: No data ingestion or loading—requires additional tools to complete the pipeline; Not a full orchestrator; enterprise use often requires Airflow or Dagster alongside; Jinja/macro templating has a steep learning curve for advanced use cases; Built-in tests are basic; deeper data quality requires extra tooling; dbt Cloud seat-based pricing scales expensively for larger teams; Cloud IDE makes bulk model edits difficult without pulling the repo locally; Documentation skews toward dbt Cloud; dbt Core users must infer feature availability; Uncertainty around open-source investment post-Fivetran merger.

When was dbt founded and where?

dbt was founded in 2016, headquartered in Philadelphia, PA, USA by Tristan Handy, Drew Banin, Connor McArthur.

dbt reports 500-1000 employees, 5,000+ paying customers; 80,000+ teams w customers, ~$100M ARR.

AI visibility report

dbt ranks #5 in Data Engineering & ETL/ELT Pipelines AI search.

Outside the top three on 17 of the 25 prompts buyers actually ask.

Airbyte is cited on 11 of those losses.

25 prompts

6 platforms

Updated Sep 29, 2026 - refreshed weekly

Track dbt daily

14-day free trial. No card required. Setup comes pre-filled for dbt.

Track dbt across these prompts daily.

Start your 14-day trial

15percent

Presence Rate

Low presence

#5 among 12 vendors · still absent from 84.7% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

#5of 12

Peer Ranking

#1#12

Mid-packin Data Engineering & ETL/ELT Pipelines

Key Metrics

Presence Rate

15.3%

Share of Voice

8.2%

Avg Position

#21.9

Docs Presence

4.7%

Blog Presence

7.3%

Brand Mentions

1.3%

Platform Breakdown

Grok

60%15/25 prompts

Perplexity

Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

dbt Labs, founded in 2016 and headquartered in Philadelphia, PA, is the company behind dbt (data build tool)—the open standard for analytics engineering and data transformation in the modern data stack. dbt enables data teams to transform raw data inside cloud warehouses using SQL and software engineering practices including version control, testing, documentation, and CI/CD deployment. The platform offers dbt Core, a free open-source framework under Apache 2.0, and dbt Cloud, a commercial SaaS product with a browser IDE, job scheduling, semantic modeling, AI assistance (dbt Copilot), and enterprise governance. With over 100,000 community members, 80,000+ teams using dbt weekly, and an estimated $100M ARR in 2024, dbt Labs is widely regarded as the de-facto industry standard for analytics engineering transformation workflows.

AI visibility report

dbt ranks #5 in Data Engineering & ETL/ELT Pipelines AI search.

Outside the top three on 17 of the 25 prompts buyers actually ask.

Airbyte is cited on 11 of those losses.

25 prompts

6 platforms

Updated Sep 29, 2026 - refreshed weekly

Track dbt daily

14-day free trial. No card required. Setup comes pre-filled for dbt.

Track dbt across these prompts daily.

Start your 14-day trial

15percent

Presence Rate

Low presence

#5 among 12 vendors · still absent from 84.7% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

#5of 12

Peer Ranking

#1#12

Mid-packin Data Engineering & ETL/ELT Pipelines

Key Metrics

Presence Rate

15.3%

Share of Voice

8.2%

Avg Position

#21.9

Docs Presence

4.7%

Blog Presence

7.3%

Brand Mentions

1.3%

Platform Breakdown

Grok

60%15/25 prompts

Perplexity

Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

Reviews

4.7/5G2·197+4.9/5Gartner Peer Insights·26+9.1/10TrustRadius·63+

Praised

SQL-first developer experience and clean project structure
Built-in testing and data quality framework
Auto-generated documentation and interactive DAG lineage
Encourages software engineering best practices (version control, CI/CD)
Thriving open-source community and documentation
Modular model architecture for managing complex transformations
Deep integration with Snowflake, BigQuery, and Databricks
Significant warehouse cost savings via stateful/incremental orchestration

dbt earns strong ratings across major review platforms, with users consistently praising its SQL-first developer experience, enforced software engineering best practices, and the quality of its open-source community and documentation. Data engineers and analytics engineers highlight the modular model structure, automatic lineage, and built-in testing as transformative for data quality and team collaboration. Common criticisms center on the narrow scope (transformation-only, requiring separate ingestion tools), the steep learning curve for Jinja/macro-based advanced use cases, the inflexibility of complex test customization, and the cost of dbt Cloud at scale. Enterprise users flag that the built-in scheduler is not a full orchestrator and that seat-based pricing can escalate for larger teams.

Prompt	Perplexity	Bing Copilot	Gemini Search	Google AI Mode	ChatGPT	Grok
Capability4/5 cited (80%)
Which data orchestration tools support complex multi-step pipelines with branching logic, sensors, and cross-team dependencies?	A competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	Your brand and a competitor were cited

#	Brand	PresencePres.	Share of VoiceSoV	DocsDocs	BlogBlog	MentionsMent.	Avg PosPos
1	Fivetran	30.7%	26.3%	18.7%	10.0%	39.3%	#26.8
2	Airbyte	24.7%	16.0%	11.3%	2.7%	39.3%	#22.2
3	Integrate.io	18.0%	15.8%	0.0%	18.0%	15.3%	#29.9
4	Matillion	16.7%	8.0%	6.7%	0.0%	20.0%	#24.1
5	dbt	15.3%	8.2%	4.7%	7.3%	1.3%	#21.9
6	Dagster	14.7%	12.3%	9.3%	4.0%	0.0%	#29.7
7	Hevo Data	6.7%	2.7%	3.3%	0.0%	10.7%	#38.5
8	Rivery	6.0%	1.6%	0.0%	2.0%	4.7%	#15.8
9	Meltano	5.3%	4.4%	2.7%	2.7%	8.0%	#35.4
10	Astronomer	4.7%	2.3%	3.3%	1.3%	6.0%	#44.5
11	Hightouch	2.0%	2.1%	2.0%	1.3%	2.7%	#28.1
12	Census	0.7%	0.2%	0.0%	0.0%	2.7%	#41.0

Developer Experience5/5 cited (100%)
What ELT platforms give data engineers the best debugging experience when a pipeline fails mid-run with partial data loaded?	A competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	Neither your brand nor a competitor was cited	Your brand and a competitor were cited	Your brand and a competitor were cited

Integrations & Ecosystem3/5 cited (60%)
Which ETL tools have an open API and SDK so we can build custom connectors for internal data sources quickly?	A competitor was cited	A competitor was cited	A competitor was cited	Your brand was cited	A competitor was cited	A competitor was cited

Performance & Reliability4/5 cited (80%)
Which ELT platforms can sync billions of rows per day from a high-volume transactional database without impacting source system performance?	A competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	Your brand and a competitor were cited

dbt ranks #5 in Data Engineering & ETL/ELT Pipelines AI search.

Key Metrics

Platform Breakdown

Overview

dbt ranks #5 in Data Engineering & ETL/ELT Pipelines AI search.

Key Metrics

Platform Breakdown

Overview

Prompts where competitors are visible and dbt is not.

Where dbt is winning5

Where dbt is losing5

Key Facts

Key Capabilities10

Key Use Cases8

dbt customer outcomes

Recent Trend

How AI describes dbt3

Most cited sources8

Alternatives in Data Engineering & ETL/ELT Pipelines6

Reviews

Pricing

Limitations

Topic Coverage

Prompt-Level Results

Vertical Ranking

Turn this into your team dashboard

Frequently asked questions

Setup & First Run1/5 cited (20%)
I'm evaluating ETL platforms for a company starting its modern data stack — which tools are fastest to onboard and connect to a cloud warehouse?	A competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited

dbt ranks #5 in Data Engineering & ETL/ELT Pipelines AI search.

Key Metrics

Platform Breakdown

Overview

dbt ranks #5 in Data Engineering & ETL/ELT Pipelines AI search.

Key Metrics

Platform Breakdown

Overview

Prompts where competitors are visible and dbt is not.

Where dbt is winning5

Where dbt is losing5

Key Facts

Key Capabilities10

Key Use Cases8

dbt customer outcomes

Recent Trend

How AI describes dbt3

Most cited sources8

Alternatives in Data Engineering & ETL/ELT Pipelines6

Reviews

Pricing

Limitations

Topic Coverage

Prompt-Level Results

Vertical Ranking

Turn this into your team dashboard

Frequently asked questions

What does dbt do?

Who is dbt best for?

How is dbt priced?

What are the alternatives to dbt?

What do users praise about dbt?

What are common complaints about dbt?

When was dbt founded and where?

How big is dbt?