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role-database:columnar-databases

Provide operational guidance for 12 columnar and wide-column databases.

14|3|Updated Feb 22, 2026
Search Tags:#analytics#data modeling#ClickHouse#database tuning#columnar databases#wide-column stores#Cassandra
One-click install
npx skills add https://github.com/rnavarych/alpha-engineer --skill role-database-columnar-databases
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: role-database:columnar-databases
Source: https://github.com/rnavarych/alpha-engineer/tree/main/plugins/roles/role-database/skills/columnar-databases
Command: npx skills add https://github.com/rnavarych/alpha-engineer --skill role-database-columnar-databases

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides deep operational guidance for 12 different columnar and wide-column databases, enabling efficient configuration, tuning, and operation for analytics or high-write workloads.

Core Features & Use Cases

  • Database Selection: Framework to choose the right columnar database based on workload, write/read patterns, latency, and scale.
  • Technology Deep Dives: Detailed information on Apache Cassandra, ScyllaDB, HBase, Bigtable, ClickHouse, Druid, StarRocks, Pinot, Vertica, and MonetDB.
  • Operational Guidance: Covers data modeling, compaction strategies, consistency levels, anti-patterns, and specific operational commands.
  • Use Case: You need to select and configure a database for a real-time analytics dashboard. This Skill helps you compare options like Druid, Pinot, and StarRocks, and provides specific tuning advice for the chosen technology.

Quick Start

Use the columnar-databases skill to compare Apache Cassandra and ClickHouse for a time-series analytics workload.

Frequently Asked Questions about role-database:columnar-databases

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose the best columnar database for real-time analytics workloads?▼

When choosing a columnar database for analytics, evaluate workload patterns, latency requirements, and scale. This Skill compares 12 columnar and wide-column databases like ClickHouse, Druid, and Pinot to help you select the right technology for your specific use case.

What is the difference between ClickHouse and Apache Cassandra for time-series data?▼

ClickHouse handles time-series analytics with fast aggregation queries, while Cassandra provides high-write throughput as a wide-column store. This Skill compares their data modeling, consistency levels, and operational tuning to guide your time-series workload implementation.

How do I configure compaction strategies in wide-column stores like ScyllaDB or HBase?▼

Configuring compaction strategies in ScyllaDB or HBase requires understanding their specific operational commands and architecture. This Skill provides detailed compaction guidance, anti-patterns, and tuning advice to optimize wide-column stores for your specific write and read patterns.

When should I use a columnar database instead of a standard relational database?▼

Use a columnar database instead of a standard relational database when you need efficient analytics, high-write workloads, or massive scale. This Skill explains when columnar formats are needed and provides operational tuning guidance for systems like Vertica and MonetDB.

What data modeling anti-patterns should I avoid with Apache Cassandra and Bigtable?▼

Data modeling anti-patterns to avoid with Cassandra and Bigtable include improper consistency levels and inefficient compaction strategies. This Skill outlines specific anti-patterns and provides operational commands to ensure correct wide-column data modeling and high-write throughput.

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