ORM Performance
===============

.. note::
   **Status:** This page is under development.

Performance characteristics and optimization techniques for the ORM API.

Overview
--------

This page focuses on performance aspects of the **ORM API**, including:

- Serialization overhead
- Index lookup performance
- Lazy loading benefits
- Batch operation patterns

For low-level LMDB performance, see :doc:`../lmdb/performance`.
For overall comparisons, see :doc:`../performance`.

Coming Soon
-----------

This page will cover:

1. **Serialization Performance**
   - JSON vs CBOR vs FlatBuffers comparison
   - Serialization overhead measurements
   - Zero-copy FlatBuffers benefits
   - NumPy array performance

2. **Lazy Loading**
   - FlatBuffers lazy deserialization
   - Property access patterns
   - Memory efficiency
   - CPU trade-offs

3. **Index Performance**
   - Index lookup overhead
   - Composite index efficiency
   - Index update cost
   - When indexes help vs hurt

4. **Batch Operations**
   - Transaction batching strategies
   - Optimal batch sizes
   - Example: pydefi batch inserts
   - Throughput measurements

5. **Background Writer Pattern**
   - Decoupling capture from persistence
   - Queue-based architecture
   - Performance gains
   - Example: pydefi order book replica

6. **Memory Efficiency**
   - Schema overhead
   - Index memory usage
   - FlatBuffers vs CBOR memory footprint
   - Large object strategies

7. **Optimization Techniques**
   - Choosing serialization formats
   - Index design for performance
   - Transaction sizing
   - Read vs write optimization

Benchmark Results
-----------------

*(Real-world benchmarks from Crossbar.io and pydefi to be added)*

**Serialization Overhead**:
   - JSON: baseline
   - CBOR: X% faster
   - FlatBuffers: X% faster
   - NumPy: X% faster

**Index Lookups**:
   - Primary key: X ops/sec
   - Simple index: X ops/sec
   - Composite index: X ops/sec

**Batch Writes**:
   - Single-record transactions: X writes/sec
   - Batched (100): X writes/sec
   - Batched (1000): X writes/sec

Comparison with Low-Level API
------------------------------

When ORM overhead matters and when it doesn't.

Real-World Performance
----------------------

**Crossbar.io** (via cfxdb):
   - Event history: X events/sec with FlatBuffers
   - Cookie lookups: X lookups/sec with indexes
   - Session tracking: X sessions/sec

**pydefi**:
   - Trade ingestion: X trades/sec with batch writes
   - Order book updates: X updates/sec with background writer
   - Real-time market data: X snapshots/sec

See Also
--------

- :doc:`serialization` - Choosing formats
- :doc:`../lmdb/performance` - Low-level performance
- :doc:`../performance` - Overall comparison
