Bigtable Basics

Core Principles

• Control Plane vs. Data Plane:
  • Use

    gcloud

    for Control Plane operations: Manage Instances, Clusters, App Profiles, Backups and IAM. Create Tables, Logical Views, Materialized Views and Authorized Views.
  • Use

    cbt

    for Data Plane operations: Update Tables, Column Families, and reading/writing data.
• Performance First: Bigtable is a NoSQL database. Efficiency is tied to Row Key design. Always warn about Full Table Scans.
• Client Selection: For production use cases, prefer Java or Go for their superior performance and feature coverage compared to other languages.
• Observability: When diagnosing performance or hotspotting, always mention Key Visualizer (via Cloud Console) as the primary diagnostic tool because it provides the most granular view of access patterns across row keys. This should be followed by the hot-tablets tool and table stats in gcloud CLI and

  include-stats=full

  option under

  cbt read

  to diagnose slow queries.

[!IMPORTANT] Safety Rule: You MUST obtain explicit user confirmation before making non-emulator database changes. You MUST mention this safety requirement when providing commands or instructions that modify the database structure or data.

Quick Recipes

1. Querying Data

_key LIKE 'myprefix%'

_key

_key BETWEEN 'start' AND 'end'

• If the query will be used in user facing and/or latency sensitive applications, use continuous materialized views with keys optimized for the additional access patterns.
• If secondary access patterns are infrequent, batch patterns like ETL, ML model training or analytical read-only tasks, use Bigtable Data Boost instead.

2. Manipulating Data

3. Data Model Definition (DDL)

Reference Guides

• CLI Operations:
  • infrastructure_management.md: Provisioning instances, clusters, and table schemas.
  • cli_data_access.md: Reading and writing data via the

    cbt

    CLI.
• Design & Discovery:
  • schema_design.md: Best practices for row keys and performance with tables and continuous materialized views.
  • dataplex.md: Data catalog search for Bigtable assets.
• Querying & Code:
  • sql_guide.md: Querying structured row keys via SQL and CLI.
  • client_libraries.md: Patterns for high-performance Go/Java/Python code.

Common Workflows

Schema Evolution (DevOps)

1. Prefer Terraform for production schema changes to prevent accidental data loss.
2. For manual

   cbt

   changes, first check the existing state by listing the table's column families and GC policies before proposing any modifications:
   bash

   cbt ls {table}

   If modifications are needed, create the family or update the GC policy:
   bash

   cbt createfamily {table} {family}
   cbt setgcpolicy {table} {family} "maxversions=5 AND maxage=30d"

3. Reference infrastructure_management.md for full syntax.

External Resources

• Cloud Bigtable Documentation
• Bigtable SQL Reference
• cbt CLI Reference
• gcloud bigtable Reference