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Future Features Roadmap

This document outlines potential features that could enhance pgsqlite by working within SQLite's constraints to provide better PostgreSQL compatibility and performance.

1. Write Queue & Batching System

Problem

SQLite only allows one writer at a time, causing "database locked" errors for concurrent writes.

Solution

  • Queue concurrent write requests instead of failing immediately
  • Batch multiple writes together in single transactions
  • Configurable batch size and time windows (e.g., batch up to 100 writes or 10ms)
  • Priority queuing for critical writes
  • Return PostgreSQL-compatible transaction IDs immediately

Benefits

  • Dramatically improved concurrent write performance
  • Better user experience (no immediate failures)
  • Optimal use of SQLite's write capabilities

2. Multi-Database Router

Problem

PostgreSQL supports multiple databases per server instance, SQLite doesn't.

Solution

  • Support CREATE DATABASE / DROP DATABASE commands
  • Map each database name to a separate SQLite file
  • Route connections based on database parameter
  • Maintain a registry of databases in a metadata SQLite file
  • Support PostgreSQL's \l command to list databases

Benefits

  • True multi-tenant isolation
  • Easy per-database backups
  • Compatible with PostgreSQL tooling expectations
  • Simple database cloning (just copy the file)

3. Read Replica Architecture

Problem

SQLite's single-writer limitation affects read scalability under write load.

Solution

  • Maintain read-only copies using SQLite's backup API
  • Route SELECT queries to replicas, writes to primary
  • Configurable replication lag tolerance
  • Automatic replica promotion on primary failure
  • Load balancing across multiple replicas

Benefits

  • Horizontal read scaling
  • Zero-downtime backups from replicas
  • Improved read performance during writes
  • High availability option

4. Smart Connection Management

Problem

Current connection handling doesn't optimize for SQLite's characteristics.

Solution

  • Separate read and write connection pools
  • Fair queuing for write operations with timeouts
  • Connection priorities and weights
  • Automatic retry with exponential backoff
  • Pre-warmed connections with cached metadata
  • Configurable max wait times

Benefits

  • Better resource utilization
  • Improved fairness under load
  • Reduced connection overhead
  • Better error handling

5. Time-Travel Queries

Problem

No built-in way to query historical data in SQLite.

Solution

  • Leverage SQLite's WAL for historical queries
  • Support: SELECT * FROM users AS OF TIMESTAMP '2024-01-01'
  • Configurable retention periods
  • Automatic old WAL cleanup
  • Optional separate history database

Benefits

  • Powerful debugging capabilities
  • Audit trail functionality
  • Undo capabilities for applications
  • Compliance with data retention requirements

6. Automatic Table Sharding

Problem

Large tables can exceed SQLite's practical size limits.

Solution

  • Transparent sharding across multiple SQLite files
  • Hash or range-based partitioning
  • Parallel query execution across shards
  • Automatic shard rebalancing
  • Shard-aware query optimization

Benefits

  • Overcome SQLite size limitations
  • Better performance for large datasets
  • Parallel query execution
  • Easier maintenance of large tables

7. Observability & Monitoring

Problem

Limited visibility into pgsqlite's operation and performance.

Solution

  • Prometheus metrics endpoint
  • Built-in query performance tracking
  • Lock contention monitoring
  • Slow query log with explain plans
  • Database growth tracking
  • Connection pool statistics
  • Cache hit rate metrics

Benefits

  • Production-ready monitoring
  • Performance troubleshooting
  • Capacity planning data
  • SLA monitoring

8. SQLite Management Interface

Problem

No easy way to manage SQLite-specific features through PostgreSQL protocol.

Solution

  • Web-based admin interface at /admin
  • PRAGMA configuration management
  • Automatic VACUUM scheduling
  • Index usage statistics
  • Visual query plan analysis
  • Live performance metrics
  • Database file management

Benefits

  • Easy SQLite administration
  • Visual performance tuning
  • Reduced operational overhead
  • Better debugging tools

9. Change Data Capture (CDC)

Problem

No native way to stream changes from SQLite.

Solution

  • Trigger-based change capture
  • Stream to Kafka/Redis/webhooks
  • Debezium-compatible format
  • Configurable filters and transformations
  • At-least-once delivery guarantees
  • Change buffering during downstream outages

Benefits

  • Enable event-driven architectures
  • Real-time cache invalidation
  • Data pipeline integration
  • Audit logging

10. Query Routing & Optimization

Problem

All queries treated equally regardless of characteristics.

Solution

  • Automatic read/write query detection
  • Route analytical queries to replicas
  • Custom routing rules via configuration
  • Query pattern learning
  • Automatic index recommendations
  • Query result pre-computation

Benefits

  • Better resource utilization
  • Improved query performance
  • Reduced primary database load
  • Self-tuning capabilities

11. Advanced Backup & Recovery

Problem

Limited backup options for production use.

Solution

  • Continuous incremental backups
  • Point-in-time recovery (PITR)
  • Backup to S3/cloud storage
  • Parallel backup streams
  • Backup verification and testing
  • One-command disaster recovery
  • Cross-region replication

Benefits

  • Production-grade data protection
  • Compliance with backup requirements
  • Minimal performance impact
  • Quick recovery options

12. Streaming & Cursors

Problem

Large result sets consume excessive memory.

Solution

  • True cursor support with DECLARE CURSOR
  • Streaming result sets
  • Configurable fetch sizes
  • Automatic pagination
  • Memory-limited result buffering
  • Async result streaming

Benefits

  • Handle arbitrary large results
  • Reduced memory usage
  • Better performance for exports
  • PostgreSQL cursor compatibility

Implementation Priorities

Phase 1: Core Enhancements (High Value, Lower Complexity)

  1. Write Queue & Batching - Immediate performance benefit
  2. Multi-Database Router - Enables many use cases
  3. Connection Management - Better concurrency handling

Phase 2: Scalability (High Value, Medium Complexity)

  1. Read Replicas - Horizontal scaling
  2. Monitoring/Metrics - Production readiness
  3. Backup & Recovery - Data safety

Phase 3: Advanced Features (Specialized Use Cases)

  1. Table Sharding - Very large datasets
  2. Time-Travel Queries - Unique capability
  3. CDC - Modern data stack integration
  4. Query Routing - Advanced optimization

Contributing

If you're interested in implementing any of these features, please:

  1. Open an issue for discussion
  2. Create a design document
  3. Get feedback before implementation
  4. Follow the contribution guidelines

These features would transform pgsqlite from a protocol adapter into a comprehensive SQLite-based data platform suitable for production workloads while maintaining SQLite's simplicity and embedded nature.