Camelot vs Tabula vs Kepler Docs — Which is Best for PDF Tables?
We compare open-source options (Camelot, Tabula) with Kepler Docs for accuracy, control, and scale.
TL;DR
If you love open-source and command line, Camelot and Tabula are solid for text-based PDFs. If you need OCR, batch, validations, mappings, and an API in one pipeline, choose Kepler Docs.
Quick Comparison
| Feature | Camelot (OS) | Tabula (OS) | Kepler Docs (SaaS) |
|---|---|---|---|
| Works on scanned PDFs (OCR) | ⚠️ Needs external OCR | ⚠️ Needs external OCR | ✅ Built-in OCR pipeline |
| Table detection modes | Lattice & Stream | Guess-based zones | Multi-pass + header/footer scrubbing |
| Batch processing | CLI loops/scripts | CLI/GUI; scripts | ✅ First-class batches & ZIP |
| Saved mappings/templates | Manual scripts | Manual scripts | ✅ Visual + versioned |
| Validations (sums/running balance) | Custom code | Custom code | ✅ Built-in rules |
When to Use Camelot
Best for: Python developers who need control and don't mind coding.
Pros
- •Free and open-source
- •Two detection modes (lattice and stream)
- •Good for structured tables in text-based PDFs
- •Programmable - can build custom workflows
Cons
- •Requires Python setup and dependencies
- •No OCR - scanned PDFs need preprocessing
- •Manual handling of multi-page stitching
- •No built-in validations or type inference
When to Use Tabula
Best for: Non-technical users who need a GUI and occasional extractions.
Pros
- •Free desktop app with GUI
- •Easy point-and-click interface
- •Good for simple rectangular tables
- •Can export to CSV, TSV, JSON
Cons
- •Limited batch processing capabilities
- •No OCR for scanned documents
- •Manual table selection for each file
- •No template saving or automation
When to Use Kepler Docs
Best for: Production workflows that need reliability, scale, and business-grade features.
Pros
- •Built-in OCR handles scanned PDFs
- •Batch processing with saved templates
- •Data validations (running balances, duplicates)
- •API for integration with existing systems
- •Type inference (dates, currency, percentages)
- •Multi-page stitching and header/footer removal
Cons
- •SaaS pricing (not free like open-source options)
- •Less control than writing custom code
Real-World Scenarios
Scenario 1: Research Project
Use Camelot if you're extracting tables from academic papers for one-time analysis.
Perfect for researchers who need to extract data from scientific papers and don't mind writing Python scripts.
Scenario 2: Monthly Reports
Use Tabula if you manually process the same report format each month.
Ideal for business users who need to extract data from regular reports and prefer a visual interface.
Scenario 3: Business Automation
Use Kepler Docs if you're processing invoices, bank statements, or financial documents at scale.
Best for companies that need to process hundreds or thousands of documents with consistent formatting and validation.
Sample PDFs Tested
We tested all three tools on various document types:
Bank Statements
Multi-page documents with running balances and complex layouts
Invoices
Line items, tax calculations, and vendor information
Scanned Financial Reports
Documents requiring OCR for text extraction
Academic Papers
Complex layouts with multiple tables and figures
Bottom Line
Our Recommendations:
- •Learning/experimenting? Start with Camelot or Tabula
- •Production business workflow? Consider Kepler Docs
- •Quick one-off conversion? Try SHRP.app for free
Questions about which tool fits your use case? Email us at hello@keplerdocs.com.