Quadratic Review 2026: AI Spreadsheet, Pricing, Python, and SQL
Analyze data with spreadsheets, AI, Python, and SQL
Who should use this?
Data analysts working in spreadsheets and Teams combining SQL and Python with cells.
Who should avoid it?
Mission-critical Excel models without compatibility testing, Sensitive databases without credential controls
What problem does it solve?
Quadratic is a collaborative AI spreadsheet that combines familiar cells and formulas with Python, JavaScript, SQL, database connections, charts, and natural-language analysis.
Would I recommend it?
Shortlist Quadratic for teams that want code and AI inside a collaborative spreadsheet. Keep source queries and generated code reviewable, reconcile decisive totals independently, restrict database credentials, and prove workbook compatibility before replacing an established spreadsheet stack.
Advisor score
Premium review framework
Quadratic is a collaborative AI spreadsheet that combines familiar cells and formulas with Python, JavaScript, SQL, database connections, charts, and natural-language analysis.
Direct verdict
Shortlist Quadratic for teams that want code and AI inside a collaborative spreadsheet. Keep source queries and generated code reviewable, reconcile decisive totals independently, restrict database credentials, and prove workbook compatibility before replacing an established spreadsheet stack.
What to verify
Import 30 representative workbooks and rebuild three recurring analyses using formulas, Python, SQL, and AI. Seed missing values, type errors, altered source schemas, malicious cell text, and contradictory totals. Compare outputs to known answers; measure compatibility, reproducibility, review time, connection security, collaboration conflicts, and credit cost.
Personal Recommendation
Shortlist Quadratic for teams that want code and AI inside a collaborative spreadsheet. Keep source queries and generated code reviewable, reconcile decisive totals independently, restrict database credentials, and prove workbook compatibility before replacing an established spreadsheet stack.
Try the recommendation
See whether Quadratic belongs in your stack
AI, formulas, Python, JavaScript, and SQL share one grid
Overall Score
- Last reviewed
- Sep 14, 2026
- Last updated
- Sep 14, 2026
Editorial Review Framework
How Quadratic scores
Who should use this?
Data analysts working in spreadsheets, Teams combining SQL and Python with cells, Collaborative exploratory analysis.
Who should avoid it?
Mission-critical Excel models without compatibility testing, Sensitive databases without credential controls
What problem does it solve?
Quadratic is a collaborative AI spreadsheet that combines familiar cells and formulas with Python, JavaScript, SQL, database connections, charts, and natural-language analysis.
Would I recommend it?
Shortlist Quadratic for teams that want code and AI inside a collaborative spreadsheet. Keep source queries and generated code reviewable, reconcile decisive totals independently, restrict database credentials, and prove workbook compatibility before replacing an established spreadsheet stack.
Overall Score
8.2
Ease of Use
8.0
AI Quality
8.0
Features
8.4
Speed
8.0
Integrations
8.2
Value for Money
8.0
Customer Support
7.8
Learning Curve
7.6
Recommended For
- Data analysts working in spreadsheets
- Teams combining SQL and Python with cells
- Collaborative exploratory analysis
Not Recommended For
- Mission-critical Excel models without compatibility testing
- Sensitive databases without credential controls
- Users treating generated analysis as verified
Recommended Because…
AI, formulas, Python, JavaScript, and SQL share one grid
Scores use a 0-10 editorial scale. The source data is maintained as 5-point review dimensions, then normalized for reader-friendly comparison.
Reusable trial worksheet
Test Quadratic before you commit
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Data analysts working in spreadsheets; Teams combining SQL and Python with cells; Collaborative exploratory analysis
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Complete three to five representative tasks with known acceptable outcomes and compare them with your current process.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: Personal is free with limited AI, sharing, files, and connections. Annual pricing lists Pro at $18 per user monthly with $20 in monthly AI credits and Business at $36 with $40 in credits; monthly billing is higher. Enterprise is custom with SSO, self-hosting, and dedicated support. Reviewed September 14, 2026.
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.2/5; AI quality 4.0/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: PostgreSQL, MySQL, Microsoft SQL Server, Excel, Google Sheets, REST APIs
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: AI credits limit usage; Generated code and analysis require review; Compatibility must be proven workbook by workbook
Loading saved worksheet… · private to this device or your optional account
Product interface evidence
Evaluation
Research-based
Price posture
From $0/month
Reviewed
2026-09-14
No authentic product screenshot is published for this review. DiscoverAI does not use generated interface images as product evidence.
Pricing
Personal is free with limited AI, sharing, files, and connections. Annual pricing lists Pro at $18 per user monthly with $20 in monthly AI credits and Business at $36 with $40 in credits; monthly billing is higher. Enterprise is custom with SSO, self-hosting, and dedicated support. Reviewed September 14, 2026.
Free plan: Yes. Personal is free with limited AI usage, sharing, files, connections, and support.
Editorial freshness
Pricing and material product claims were checked September 14, 2026.
Pros & Cons
Pros
- AI, formulas, Python, JavaScript, and SQL share one grid
- Useful free personal plan
- Self-hosting is available
Cons
- AI credits limit usage
- Generated code and analysis require review
- Compatibility must be proven workbook by workbook
Best For
Community evidence
How verified users put Quadratic to work
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
No approved community evidence yet. Be the first verified user to contribute.
Key Features
- AI spreadsheet
- Python
- JavaScript
- SQL
- Database connections
- Collaboration
Integrations
- PostgreSQL
- MySQL
- Microsoft SQL Server
- Excel
- Google Sheets
- REST APIs
FAQs
What is Quadratic?
Quadratic is a collaborative AI spreadsheet that combines familiar cells and formulas with Python, JavaScript, SQL, database connections, charts, and natural-language analysis.
How much does Quadratic cost?
Personal is free with limited AI, sharing, files, and connections. Annual pricing lists Pro at $18 per user monthly with $20 in monthly AI credits and Business at $36 with $40 in credits; monthly billing is higher. Enterprise is custom with SSO, self-hosting, and dedicated support. Reviewed September 14, 2026.
Who should use Quadratic?
Data analysts working in spreadsheets, Teams combining SQL and Python with cells, Collaborative exploratory analysis.
What should buyers test before choosing Quadratic?
Import 30 representative workbooks and rebuild three recurring analyses using formulas, Python, SQL, and AI. Seed missing values, type errors, altered source schemas, malicious cell text, and contradictory totals. Compare outputs to known answers; measure compatibility, reproducibility, review time, connection security, collaboration conflicts, and credit cost.
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