William Dealtry - Data persistence with consistency and performance in a truly serverless system

ArcticDB is a Python-first data frame database designed for high-performance data persistence in serverless environments, focused on finance industry use cases

Key features include:

• Schema-less storage with multi-dimensional data support
• Versioning and time travel capabilities
• Immutable data blocks to prevent corruption
• Support for various storage backends (S3, Azure, local)
• Lazy query evaluation with vectorized execution

Architecture highlights:

• Uses structured keys and version keys for data organization
• Implements persistent B-trees for efficient data access
• Employs ECS (Entity Component System) architecture
• Supports spill-to-storage for handling large datasets
• Hybrid storage approach combining fast and slow storage tiers

Performance optimizations:

• Parallel vectorized execution pipeline
• Efficient compression and data transformation during read/write
• Minimal metadata overhead
• Smart chunking and block management
• In-memory processing with storage spillover capability

Data consistency features:

• ACID compliance for data operations
• Atomic updates without data races
• Immutable storage model prevents corruption
• Version tracking and history preservation
• Consistent schema enforcement per data frame

Practical benefits:

• No server maintenance required
• Python-native interface
• Compatible with pandas, pyarrow, and polars
• Easy scaling with cloud storage
• Cost-effective storage management options