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bigtable-basics

Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable

Install / Use

npx skills add google/skills --skill bigtable-basics

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

84/100

Category

Automation

Supported Platforms

Universal

Our assessment of bigtable-basics

bigtable-basics scores 84/100 on our quality scale, 887th of 1,411 Automation skills we index.

Its SKILL.md is 5.0 KB long, well organised into 10 sections and no code examples: a solid amount of guidance for an agent.

With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
13/20
Description
12/15
Adoption
18/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 3 days ago, so bigtable-basics is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

bigtable-basics compared with similar skills

All 4 of these similar skills score higher than bigtable-basics; compare them before choosing.

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bigtable-basics (this skill)by google8420.3k3d agoSKILL.md
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Frequently asked questions

How do I install bigtable-basics?
Run npx skills add google/skills --skill bigtable-basics. The install tabs above show the steps for each supported agent.
Which AI agents does bigtable-basics work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is bigtable-basics safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is bigtable-basics still maintained?
The repository was last updated 3 days ago, so bigtable-basics is actively maintained.

name: bigtable-basics metadata: version: "1.0.0" category: Databases description: >- Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration.

Bigtable Basics

This skill provides core workflows and guidance for administering and developing with Google Bigtable.

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

Use SQL for complex transforms or aggregations and key-value APIs for simpler query patterns. Note: Use exact match, prefix (_key LIKE 'myprefix%'), or range predicates on _key to avoid expensive unbounded scans. Recommend explicit row ranges (_key BETWEEN 'start' AND 'end') as a more performant alternative to prefix matches where possible.

If expensive scans (either unbounded or prefix or range queries scanning a large range) are unavoidable due to multiple access patterns that can’t all be accommodated in a single schema, consider one of these two options:

  • 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

Use key-value APIs for insert, update, increment and delete operations. SQL API is read-only.

3. Data Model Definition (DDL)

SQL API doesn't support DDL operations. Table creation, deletion, updates should be made using gcloud CLI. Logical Views and Continuous Materialized Views are defined as SQL queries but they must be created using gcloud CLI.

Reference Guides

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:

    cbt ls {table}
    

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

    cbt createfamily {table} {family}
    cbt setgcpolicy {table} {family} "maxversions=5 AND maxage=30d"
    
  3. Reference infrastructure_management.md for full syntax.

External Resources

Related Skills

View on GitHub
GitHub Stars20.3k
CategoryAutomation
Updated3d ago
Forks1.7k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions