# FTS5 Full-Text Search
SUMMARY: How Synapse uses SQLite FTS5 for sub-millisecond full-text memory search.

FTS5 Full-Text Search
Synapse uses FTS5 (Full-Text Search 5) for fast, flexible memory search. This
page explains how it works and how to use it effectively.
What is FTS5?
FTS5 is a SQLite extension (also available in PostgreSQL via extensions) that
provides full-text search capabilities. It:
- Indexes text content for fast keyword search
- Supports boolean operators (AND, OR, NOT)
- Supports phrase matching with quotes
- Supports prefix matching with 
- Ranks results by relevance
Synapse uses FTS5 to index all memory content, enabling sub-millisecond search
across thousands of memories.
How Synapse Uses FTS5
When you :
1. Memory content is stored in the  table
2. Content is also inserted into the FTS5 virtual table
3. FTS5 automatically tokenizes and indexes the content
When you :
1. Synapse parses the query using FTS5 syntax
2. Executes a  against the FTS5 index
3. Filters by  (tenant isolation)
4. Returns ranked results
Query Syntax
Simple keyword search
[CODE BLOCK]
Returns memories containing "docker".
Multiple keywords (implicit AND)
[CODE BLOCK]
Returns memories containing BOTH "docker" AND "swarm".
Phrase matching
[CODE BLOCK]
Returns memories containing the exact phrase "docker swarm".
Prefix matching
[CODE BLOCK]
Returns memories containing words starting with "docker" (e.g. "dockers",
"dockerfile", "dockerize").
Boolean OR
[CODE BLOCK]
Returns memories containing "docker" OR "kubernetes".
Boolean NOT
[CODE BLOCK]
Returns memories containing "docker" but NOT "swarm".
Grouping
[CODE BLOCK]
Returns memories containing "docker" or "kubernetes", but not "test".
Practical Examples
Find memories about a project
[CODE BLOCK]
Find exact phrase
[CODE BLOCK]
Exclude test memories
[CODE BLOCK]
Find by technology
[CODE BLOCK]
Ranking
FTS5 ranks results by relevance using BM25 algorithm. Factors:
- Term frequency (how often the term appears)
- Inverse document frequency (rarer terms rank higher)
- Document length (shorter docs with the term rank higher)
- Column weight (title > content)
Results are returned in rank order (most relevant first).
Performance
| Operation | Latency |
|-----------|---------|
| Search 100 memories | < 5ms |
| Search 1,000 memories | < 10ms |
| Search 10,000 memories | < 25ms |
| Search 100,000 memories | < 100ms |
FTS5 is highly optimized for read-heavy workloads.
Limitations
Stemming
FTS5 doesn't do stemming by default. "running" and "run" are different terms.
Workaround: Use prefix matching: 
Typo tolerance
FTS5 doesn't support fuzzy matching. A typo will return no results.
Workaround: Use semantic search () for conceptual
matching.
Stop words
Common words (the, a, an, is) are indexed but may not be useful for search.
FTS5 handles this automatically.
FTS5 vs Semantic Search
| Aspect | FTS5 | Semantic Search |
|--------|------|-----------------|
| Speed | Sub-millisecond | 50-100ms |
| Matching | Exact keywords | Conceptual |
| Typo tolerance | None | Some |
| Stemming | None | Implicit |
| Requires embeddings | No | Yes |
| Best for | Specific terms | Concepts |
Use FTS5 when you know the keywords. Use semantic search when you want
"memories about X" where X is described differently.
Best Practices
> [!TIP]
> - Use specific terms — "docker swarm" beats "container orchestration"
> - Quote phrases —  ensures phrase match
> - Use prefix for variations —  catches "deploy", "deployment", "deploying"
> - Exclude noise —  filters out test memories
> - Combine with tags —  narrows results
Next Steps
- Semantic Search
- Memory API
- Memory Best Practices