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# JSONite: High-Performance Embedded Database for Semi-Structured Data
---
## The JSON Performance Crisis
**JSON is Everywhere:**
- Web APIS, IoT, logs, configurations
- Semi-structured, flexible, human-readable
**But Current Solutions Fail:**
- **Large Databases**: People use MongoDB or PostgreSQL's JSONB to store data
- **Embeded Databases**: RocksDB and PoloDB lack of ACID and SQL support
- **Serialization to String**: Or serialize JSON into strings and store in SQLite
Serialized JSON with SQL example
```sql
insert into http_request_log (ip, headers)
values ('127.0.0.1', '{
"Content-Type": "application/oct-stream",
"X-Forwarded-For": "100.64.0.1",
}');
```
---
## Introducing JSONite
**Best of Both Worlds:**
- SQLite's based
- Native JSON optimization
**Key Advantages:**
- ✅ ACID compliance
- ✅ SQL simplicity
- ✅ Serverless C library
- ✅ Lightning-fast JSON access
---
## Smart Key Optimization
**Key Sorting by Length:**
```
{
"id": 1,
"address": {...}
"name": "John",
"email": "john@example.com",
}
```
**Sorted as:**
```
{
"id", (2 chars)
"name", (4 chars)
"email", (5 chars)
"address", (7 chars)
}
```
**Binary search on length → Fast lookups**
---
## Handling Massive Data: Smart TOAST
**The Oversized-Attribute Storage Technique**
- Standard approach: arbitrary chunking
- JSONite's innovation: **Data-Type Aware TOAST**
**Intelligent Chunking:**
- Arrays split between elements
- Objects split between key-value pairs
- Text falls back to fixed chunks
**Enables "Slice Detoasting":**
- `$.logs[1000000:1000010]` fetches only 10 elements
- Not the entire multi-gigabyte array
Smart Chunking Example
```json
{
"id": 1,
"title": "some text",
"html": <pointer to TOAST of 200k text>,
"photos": [<pointer to TOAST of binary data>],
"crawl_logs": [<pointer to TOAST of array of texts>]
}
```
---
## Query Power
**Full SQL + JSON Support:**
- PostgreSQL-compatible JSONB path operators
- GIN indexes for instant search
```sql
SELECT *
FROM accounts
WHERE data @> '{"status": "active"}'
```
---
## Performance Validation: Benchmark Datasets
**Three Specialized Workloads:**
1. **YCSB-Style Read Benchmark**
- Yahoo! Cloud Serving Benchmark
- 1M JSON documents (1KB-100KB each)
2. **TPC-C Inspired Update Benchmark**
- Transaction Processing Performance Council
- 100K transactional JSON records
- Frequent small field updates
3. **Large-Array Slice Benchmark**
- Multi-gigabyte JSON documents
- Massive arrays (10M+ elements)
**Comparison Targets:** SQLite JSONB vs MongoDB vs PostgreSQL vs JSONite
---
## JSONite: The Future of Embedded Data Storage
**Why It Matters Today:**
- **Edge Computing**: Lightweight, handles sensor data efficiently
- **Modern Apps**: SQL power + JSON flexibility, no schema migrations
**The Vision:**
- Open source implementation
- Community-driven development
- Becoming the default choice for embedded JSON storage
- Bridging SQL reliability with NoSQL flexibility
---
## Thank You
**Questions?**
*CHEN Yongyuan*
*2025-11-01*