Versioned Table

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SUMMARY

A versioned table is a database table that maintains a history of all changes, allowing access to data as it existed at any point in time. Each modification creates a new version or snapshot while preserving previous states, enabling time travel queries and audit capabilities.

How versioned tables work

Versioned tables track changes through a series of immutable snapshots, each representing the table's state at a specific point in time. This is achieved through:

  1. Version tracking - Each change creates a new version number
  2. Snapshot management - Previous versions remain accessible
  3. Metadata tracking - Changes are logged with timestamps and user information

Next generation time-series database

QuestDB is an open-source time-series database optimized for market and heavy industry data. Built from scratch in Java and C++, it offers high-throughput ingestion and fast SQL queries with time-series extensions.

Key features and capabilities

Snapshot isolation

Versioned tables provide snapshot isolation for readers, ensuring consistent views of data without blocking writers. This enables:

  • Concurrent access to different versions
  • Point-in-time recovery
  • Reproducible analytics

Time travel queries

Users can query historical states using:

-- ⚠️ ANSI (requires QuestDB adaptation)
SELECT * FROM my_table AT TIMESTAMP '2023-01-01 12:00:00';

This capability is particularly valuable for:

  • Audit compliance
  • Bug investigation
  • Historical analysis

Next generation time-series database

QuestDB is an open-source time-series database optimized for market and heavy industry data. Built from scratch in Java and C++, it offers high-throughput ingestion and fast SQL queries with time-series extensions.

Implementation approaches

Copy-on-write

Copy-on-write maintains full copies of modified data for each version:

  1. Creates new physical copies for changed records
  2. Preserves original data intact
  3. Provides direct access to any version

Merge-on-read

Merge-on-read stores changes as deltas:

  1. Records modifications separately
  2. Reconstructs versions at query time
  3. Optimizes storage space

Applications in time-series data

In time-series contexts, versioned tables are particularly valuable for:

  • Financial audit trails
  • Industrial sensor data corrections
  • Regulatory compliance reporting

The ability to access historical states helps organizations maintain data lineage and meet compliance requirements while enabling advanced analytics capabilities.

Best practices

  1. Version retention policies

    • Define clear lifecycle rules
    • Balance history depth vs storage costs
    • Align with compliance requirements
  2. Performance optimization

    • Index version metadata
    • Optimize storage layout
    • Consider compression strategies
  3. Governance controls

    • Implement version access controls
    • Track version provenance
    • Document version changes

Integration with modern data architectures

Versioned tables are fundamental to modern data architectures, particularly in:

They provide the foundation for reproducible analytics and robust data governance strategies.

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