The Schema Markup Validator (SMV) replaced Google’s Structured Data Testing Tool on August 9th, 2021, after SEO experts highlighted issues with the Rich Results Test’s schema-checking abilities. This shift is key in the debate of Structured Data Testing Tool vs. Schema Markup Validator.
SDTT worked great since 2009 for checking structured data. The new SMV works differently – it checks if your schema markup follows schema.org rules but skips rich results testing that SDTT offered.
Both tools check schema markup differently. SDTT gives you rich results validation while SMV sticks to basic schema rules. This guide shows you exactly which tool matches your schema testing needs.
Schema Validation Tools Timeline
Schema-checking tools changed a lot between 2020-2025. The Structured Data Testing Tool started it all, but Google’s decisions changed everything about how we check schema markup.
SDTT Makes Way for New Tools
Google planned to remove SDTT in 2020. SEO experts weren’t happy with the Rich Results Test’s limits, so Google changed plans. Instead of killing SDTT completely, they teamed up with Schema.org to build something new.
This team effort created the Schema Markup Validator, launching August 9th, 2021. SMV kept what made SDTT great – easy use and technical accuracy. It also added better ways to check Schema.org markup on web pages.
SMV works differently from SDTT. It doesn’t care which search engine you use – it just checks if your schema follows the basic rules. You won’t see Google-specific warnings or preview snippets anymore like SDTT showed.
Structured Data Testing Tool vs. Schema Markup Validator: Big Updates from 2020-2025
Schema validation changed completely during these years. JSON Schema’s 2020-12 update brought major changes:
- New array setup: Changed items and additional items to prefixItems and items
- Dynamic reference system: Added $dynamicRef and $dynamicAnchor
- Better media handling: Updated schema media types
- Improved vocabulary: Split format rules into separate parts
The newer JSON Schema versions made validation more complex. Dynamic references in the 2020-12 version really changed how schema processing works.
Error messages got better too. Modern tools tell you exactly what’s wrong and handle complex schemas better.
Schema validation tools kept up with growing schema complexity. The JSON-LD usage on mobile device homepages increasing from 34% in 2021 to 37% in 2022 shows more websites need good schema-checking tools.
Core Features Face-Off
Both tools check schema markup differently. Let’s see what each one does best.
What They Check
SMV focuses on schema.org rules and syntax. The tool checks JSON-LD, RDFa, and Microdata markup. SMV makes sure your Schema.org types match common patterns.
SDTT checks more things than SMV. The tool handles all schema types, even ones Google doesn’t support. SDTT tests both schema.org rules and Google’s own requirements.
Structured Data Testing Tool vs. Schema Markup Validator: How They Look
SMV looks just like SDTT. The tool splits your screen into:
- HTML code on the left
- Schema details on the right
- Quick testing for URLs and code
Error Messages
Each tool shows errors differently. SMV points out the wrong syntax and shows your structured data summary. The tool skips warning messages and sticks to basic syntax checking.
SDTT gave you more details about errors:
- Instant feedback while testing
- Errors shown line by line
- Tips to fix problems
Working with Other Tools
These tools connect to other services differently. SMV runs on Google’s servers as part of Schema.org. It uses Google’s system to process schema markup.
SDTT worked better with Google Search Console, letting you track schema performance in search results. This made it easier to handle schema markup on big websites.
Both tools let you:
- Test live webpage URLs
- Check code snippets
- Handle different schema types
Schema Testing Steps: Structured Data Testing Tool vs. Schema Markup Validator
Schema testing works better when you know exactly what to check. SMV gives you multiple ways to test your schema markup.
SMV Testing Steps
You get two testing methods with SMV. Drop your webpage URL or paste your schema code directly. The URL method works best since it stops code errors before they start.
SMV shows your results in two parts:
- Schema markup on the left side
- Test results on the right side
Your test ends with a full report. Zero errors means perfect schema markup. Click any error message to see exactly where your markup needs fixed.
Complex Schemas Testing
Big websites need bigger schemas, making testing trickier. SMV handles tough schemas through:
- Structure Checks
- Matches Schema.org rules
- Tests nested data parts
- Checks if-then rules work right
- Format Tests SMV works with these formats:
- JSON-LD
- RDFa
- Microdata
Tough schemas need extra attention. SMV first checks if your data matches the rules. Then it makes sure everything fits together right for clean data sharing.
SMV looks for:
- Right data types
- Field rules
- Format matches
The tool handles changing schemas too. This helps when your schema needs grow or you run multiple versions at once.
SMV spots API problems early. It matches API data against your schema rules, catching issues before they break your site. This keeps your data clean and reliable across your whole system.
Schema Testing Problems
Schema testing gets tricky sometimes. Both SMV and SDTT run into different problems when checking your schema markup.
Structured Data Testing Tool vs. Schema Markup Validator: Common Errors and Fixes
Schema errors usually start with the wrong structure or bad characters. You’ll face these problems most often:
Data Format Problems Complex data structures with nested parts cause validation errors. Watch out for:
- Wrong data types in your fields
- Missing must-have elements
- Schema version mismatches
Multiple Source Issues Your schema checking gets harder with more data sources. Keep an eye on:
- Different data source formats
- Mismatched data types
- Schema changes over time
Tool Limits
SMV doesn’t do everything SDTT did. The biggest change – SMV skips warning messages and only checks basic schema rules.
SMV’s Current Limits: SMV runs in beta mode with these limits:
- No warning messages
- Basic syntax checking only
- Skips rich result checks
SDTT’s Old Problems: SDTT had its own issues too:
- Hard to edit and retest markup
- Slow testing for big schemas
- Missing support for some schemas
Search engines often read schema markup differently. You need technical know-how and careful testing to keep your search visibility strong.
Fix these limits by testing smart. Check your markup on different devices. Use Google Search Console’s ‘Enhancements’ section to catch schema errors fast.
Watch your data quality when testing schema. Moving between schemas might break things or lose data. Regular testing keeps your schema working right.
Picking Your Schema Tool: Structured Data Testing Tool vs. Schema Markup Validator
Your schema checking needs to determine which tool works best. Different businesses need different tools based on what they do.
Business Size Matters
Small businesses work fine with simple schema checks. Big companies handling lots of data need better tools with:
- Profile checking features
- Auto-testing setup
- Full documentation
Medium businesses need something in between. The right tool should make schema checking easy without creating extra work.
Schema Complexity
Your data setup changes which tool you pick. Look at these points when choosing:
- System Fit
- Works with your current tools
- Handles batch and live checks
- Good help docs and community
- Check Types How often you move data matters. Businesses moving data lots should pick tools that check automatically.
- Data Formats Your tool needs to handle:
- Connected data pieces
- Data changes
- Quality rules
Money Matters
Schema tools cost different amounts. Big tools like Informatica cost $2,000 monthly. AWS Labs gives Deequ free. Hevo Data sits in the middle at $239 per month.
Check these costs:
- Monthly fees vs one-time costs
- School discounts
- Help desk access
- Community help
Pick what fits your budget and needs. Schools might pay less with education discounts. Think about both now and later costs.
Tool prices change based on:
- Your type of business
- How many people need it
- What help do you want
Data-heavy jobs need tools that grow with you but still work right. Pick something that matches your needs while fitting your budget.
Structured Data Testing Tool vs. Schema Markup Validator: Quick Facts
| What They Do | SDTT | SMV |
| Started | 2009 | August 9th, 2021 |
| Checks | All schemas + Google rules | Just schema.org rules and syntax |
| Formats | Many schema types | JSON-LD, RDFa, Microdata |
| Error Messages | – Live testing- Line-by-line errors- Fix suggestions | – Syntax error checks- Schema data summary- No warnings |
| Works With | Connects to Google Search Console | Google’s Schema.org tool |
| Rich Results | Checks rich results | Skips rich results |
| Screen Layout | – URL testing- Code testing- Full checking | – HTML on left- Schema on right- One-click tests |
| Problems | – Slow with big schemas- Hard to edit and retest- Missing some schema types | – Beta version- No warnings- Basic syntax only |
| Search Focus | Google only | Works with any search engine |
The Final Word
SDTT and SMV excel at different things. SDTT checks everything – rich results, schema rules, and Google requirements. SMV sticks to schema.org rules and basic syntax checks.
SMV works great for small websites and developers who need basic schema checking. Big websites need extra tools alongside SMV. Missing warnings and rich results checking make SMV less powerful than SDTT.
Pick your tool based on what you need. Want simple schema.org checks? SMV does the job. Need detailed schema testing with Google Search Console? SDTT worked better, even though Google doesn’t support it anymore.
Schema tools keep changing as websites use more structured data. Right now, using both tools gives you the best schema-checking setup. This way, you catch every possible schema problem.
