How much does TextQL cost?

Analyst costs $0 monthly, Team costs $250, and Enterprise is custom. Every tier also meters compute at $0.003 per ACU.

Is TextQL open source?

No. TextQL's production platform is proprietary. The company released a smaller standalone research agent, Ana Small, as open source in March 2025.

Does TextQL replace Looker or dbt?

TextQL positions its Ontology as a replacement for dbt's Semantic Layer and LookML. Teams should expect to rebuild that modeling logic.

All comparisons

Dot vs TextQL

Dot works from the dbt and Looker models you already maintain. TextQL starts with a new Ontology.

What are the differences between Dot and TextQL?

Showing 8 of 43 capabilities across 6 categories

03 / 10

Which data sources can it access?

Automatically routes questions to the right data

Dot: Yes. Routes each question across connected sources automatically
TextQL: Partly. Routes questions, but connectors may need selection Source

04 / 10

Which business context grounds its answers?

Grounded in LookML

Dot: Yes. Grounds directly on existing Looker/LookML explores
TextQL: Partly. Listed as integration; no LookML connector documented Source

Other semantic layers

Dot: Yes. Also grounds on Cube and Steep semantic layers
TextQL: Partly. Can query a connected Cube semantic layer directly Source

05 / 10

How do you know the data is correct?

Regression tests for important questions

Dot: Yes. Per-org eval suites with feedback-driven improvement
TextQL: Partly. Observability tracks errors and frustration, not eval suites Source

07 / 10

Which outputs can it produce?

Conditional alerts and monitoring

Dot: Yes. Conditional alerts fire only when threshold met
TextQL: Partly. Playbooks surface anomalies inline; no threshold-alert system Source

White labeling and embedded analytics

Dot: Partly. Dashboard embedding; limited white-label controls
TextQL: Yes. White-label embedded dashboards and data apps Source

08 / 10

Which governance and security controls are included?

Self-hosting available

Dot: Partly. Self-hosted option, Enterprise tier only
TextQL: Yes. On-prem, BYOC, and air-gapped at Enterprise tier Source

10 / 10

How do pricing and cost controls work?

Hard usage limits, spend visibility, and ROI

Dot: Yes. Set usage limits; track spend and ROI
TextQL: Partly. Seat or contract limits; ROI tracked separately Source

Across all 43 capabilities

Dot36 supported2 partial5 not available

TextQL32 supported6 partial5 not available

Category	Decision point	Dot	TextQL
03 / 10Which data sources can it access?	Automatically routes questions to the right data	Yes. Routes each question across connected sources automatically	Partly. Routes questions, but connectors may need selection Source
04 / 10Which business context grounds its answers?	Grounded in LookML	Yes. Grounds directly on existing Looker/LookML explores	Partly. Listed as integration; no LookML connector documented Source
04 / 10Which business context grounds its answers?	Other semantic layers	Yes. Also grounds on Cube and Steep semantic layers	Partly. Can query a connected Cube semantic layer directly Source
05 / 10How do you know the data is correct?	Regression tests for important questions	Yes. Per-org eval suites with feedback-driven improvement	Partly. Observability tracks errors and frustration, not eval suites Source
07 / 10Which outputs can it produce?	Conditional alerts and monitoring	Yes. Conditional alerts fire only when threshold met	Partly. Playbooks surface anomalies inline; no threshold-alert system Source
07 / 10Which outputs can it produce?	White labeling and embedded analytics	Partly. Dashboard embedding; limited white-label controls	Yes. White-label embedded dashboards and data apps Source
08 / 10Which governance and security controls are included?	Self-hosting available	Partly. Self-hosted option, Enterprise tier only	Yes. On-prem, BYOC, and air-gapped at Enterprise tier Source
10 / 10How do pricing and cost controls work?	Hard usage limits, spend visibility, and ROI	Yes. Set usage limits; track spend and ROI	Partly. Seat or contract limits; ROI tracked separately Source
Across all 43 capabilities		Dot36 supported2 partial5 not available	TextQL32 supported6 partial5 not available

Conclusion

Choose for the analytics stack you want to end up with

The decision is not only which tool answers questions today. It is which product can become your analytics platform over time.

Choose TextQL for lightweight analysis and embedded data apps

Compute costs $0.003 per ACU, about 83,000 per $250.
Over 50 connectors include SAP HANA, Oracle, Salesforce, and Jira.
Ontology changes use GitHub pull requests and branch protection.

Pricing

Analyst costs $0 plus compute and includes three seats.
Team costs $250 monthly plus compute, with unlimited seats.
Enterprise pricing is custom for dedicated, on-premises, or BYOC deployment.

Source

Choose Dot for best-of-breed AI analytics that can replace BI

Connect Dot to the data sources and semantic models you already have, then start with one agent. Context, apps, and business logic stay version-controlled in a repository you own, so they never become a Dot-only asset. Add dashboards, reporting, and governed workflows as adoption grows, then retire BI software you no longer need.

Watch out

Dot is growing quickly. Its smaller team may not offer the same level of hands-on support as a larger vendor in every region.

Pricing

Free plan, no credit card
Pro at $200/month, or $180/month billed annually. Unlimited users.
Team at $800/month, or $720/month billed annually. Adds single sign-on and row-level security.
Enterprise is custom: self-hosting, SLAs, and volume terms

Full pricing

Why the pricing model matters

Frontier AI has variable inference cost. A vendor that relies only on seat pricing must eventually meter AI, absorb the cost, or limit capability. Dot makes usage visible, lets teams set limits, and tracks the return on that spend.

Receipts

Benchmarked against human analysts, and measured in production

DABStep is Adyen’s public data-analysis benchmark. Dot scored above trained human analysts. It is independently published and available to inspect. In production, customers report these outcomes.

18× ROI

Choco, from time saved on analytics

12,000+ hours

saved every year at Duolingo, across 5,000+ tables

99% faster

time-to-insight at Emerge

€800K found

in a single investigation at KRY

Every Dot answer shows its work. Click any number to inspect the query.