XML vs TONL: Data Format Comparison for AI Applications
Compare XML vs TONL for LLM applications: query capabilities, streaming, schema validation, and advanced optimization strategies.
While XML offers mature tooling like XPath and XSD, TONL provides a modern alternative with built-in query APIs, streaming support, and advanced optimization. For LLM applications requiring both efficiency and powerful data manipulation, TONL delivers enterprise-grade capabilities with up to 69% token savings.
The Contenders
XML
Pros:
- Mature ecosystem with XPath, XSLT, XSD.
- Industry standard for enterprise integrations.
- Strong schema validation capabilities.
- Streaming parsers available (SAX, StAX).
Cons:
- Extreme verbosity and token overhead.
- Complex query syntax (XPath learning curve).
- No built-in optimization strategies.
- Memory-intensive for large documents.
TONL
Pros:
- Built-in JSONPath-like query API.
- Native streaming for multi-GB files.
- Schema validation with TSL (13 constraints).
- Advanced optimization (dictionary, delta, RLE).
Cons:
- Newer format, growing ecosystem.
- No XSLT-equivalent transformation language.
- Requires migration from XML workflows.
Query Capabilities Comparison
Both formats offer query capabilities, but with different approaches and complexity levels.
XML with XPath:
// Select all user names
//user/name/text()
// Filter by role
//user[role='admin']/name
// Complex nested query
//orders/order[total > 100]/items/item[quantity > 5]TONL Query API:
// Select all user names
doc.query('users[*].name');
// Filter by role
doc.query('users[?(@.role == "admin")].name');
// Aggregation (not available in XPath)
doc.sum('orders[*].total');
doc.avg('orders[*].items[*].quantity');
doc.groupBy('users[*]', 'role');
// Fuzzy matching (unique to TONL)
import { fuzzySearch } from 'tonl/query';
fuzzySearch('Jon', ['John', 'Jane', 'Bob']);Syntax Comparison
XML Example (267 bytes, ~160 tokens):
<?xml version="1.0" encoding="UTF-8"?>
<users>
<user>
<id>1</id>
<name>Alice</name>
<role>admin</role>
</user>
<user>
<id>2</id>
<name>Bob</name>
<role>user</role>
</user>
</users>TONL Example (105 bytes, ~49 tokens - 69% reduction):
#version 1.0
users[2]{id:u32,name:str,role:str}:
1, Alice, admin
2, Bob, userAdvanced Features
Schema Validation
XML (XSD):
<xs:schema>
<xs:element name="user">
<xs:complexType>
<xs:sequence>
<xs:element name="id"
type="xs:integer"/>
<xs:element name="name">
<xs:simpleType>
<xs:restriction
base="xs:string">
<xs:minLength
value="3"/>
<xs:maxLength
value="20"/>
</xs:restriction>
</xs:simpleType>
</xs:element>
</xs:sequence>
</xs:complexType>
</xs:element>
</xs:schema>TONL (TSL):
@schema v1
@strict true
User: obj
id: u32 required
name: str required
min:3 max:20
email: str required
pattern:email
roles: list<str>
required min:1Optimization Strategies
TONL includes built-in optimization that XML lacks:
| Strategy | Description | Savings |
|---|---|---|
| Dictionary Encoding | String deduplication with references | 30-50% |
| Delta Encoding | Sequential value compression | 40-60% |
| Bit Packing | Boolean/small int compression | 87.5% |
| Run-Length Encoding | Repetitive value compression | 50-80% |
Streaming Comparison
Both formats support streaming, but with different approaches:
- XML (SAX/StAX): Event-based parsing, complex callback handling, no built-in query during stream.
- TONL: Native streaming with query support, handles multi-GB files with minimal memory, automatic chunking.
Performance Benchmarks
| Metric | XML | TONL | Improvement |
|---|---|---|---|
| Token Count (100 records) | 6,500 | 1,980 | 70% |
| Encoding Speed | 1.0x | 12-15x | 12-15x faster |
| Query Execution | XPath (slow) | Native (fast) | 5-10x faster |
| Monthly Cost (10K req) | $650 | $198 | $5,424/year |
When to Use Which?
Stick with XML if:
- You need XSLT transformations or complex XPath queries.
- Enterprise systems mandate XML (SOAP, HL7, etc.).
- You require XML-specific features (attributes, namespaces).
- Regulatory compliance requires XML format.
Switch to TONL if:
- You need both token efficiency AND query capabilities.
- You're building LLM-powered data pipelines.
- You work with large datasets requiring streaming.
- You want built-in optimization without external tools.
- Schema validation with simpler syntax appeals to you.
Final Verdict
XML remains the standard for enterprise integrations and systems requiring XSLT transformations. However, for modern LLM applications, TONL provides a compelling alternative with native query APIs, streaming support, and advanced optimization—all while delivering 70% token savings.
For simpler use cases focused purely on token efficiency, see our XML vs TOON comparison. Learn more about TONL features or explore API cost optimization strategies.