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role-database:time-series-databases

Guide selection, design, and optimization for 14 time-series databases.

14|3|Updated Feb 22, 2026
Search Tags:#database#time-series#iot#prometheus#timescaledb#influxdb#kdb+
One-click install
npx skills add https://github.com/rnavarych/alpha-engineer --skill role-database-time-series-databases
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: role-database:time-series-databases
Source: https://github.com/rnavarych/alpha-engineer/tree/main/plugins/roles/role-database/skills/time-series-databases
Command: npx skills add https://github.com/rnavarych/alpha-engineer --skill role-database-time-series-databases

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides deep operational guidance for 14 time-series databases, enabling efficient storage and retrieval of time-stamped data for metrics, IoT, and financial applications.

Core Features & Use Cases

  • Database Selection: Offers a matrix to choose the best time-series database (TSDB) based on use case, ingestion needs, and management options.
  • Operational Principles: Details core TSDB best practices, including cardinality management, retention tiers, and downsampling strategies.
  • Use Case: When designing a system to store and analyze high-frequency financial tick data, this Skill helps select the optimal TSDB (e.g., KDB+) and outlines the necessary data modeling and operational considerations.

Quick Start

Use the time-series databases skill to compare InfluxDB 3.0 and Prometheus for metrics storage.

Frequently Asked Questions about role-database:time-series-databases

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

FAQPage Schema
How do I choose the best time-series database for high-frequency financial data?▼

To choose a time-series database for financial data, use a selection matrix to compare options like KDB+ against your ingestion needs. This guidance details data modeling and operational considerations specifically for high-frequency financial workloads.

What is the best way to handle high cardinality tags in Prometheus or InfluxDB?▼

Handling high cardinality tags in time-series databases requires strict cardinality management. This guidance details core operational principles to control tag cardinality, preventing memory bloat and query degradation in TSDBs like Prometheus and InfluxDB.

How do I configure data retention and downsampling in TimescaleDB or QuestDB?▼

Configuring data retention and downsampling in time-series databases involves setting up retention tiers and aggregation strategies. This guidance provides operational best practices for implementing these storage optimization patterns in TSDBs like TimescaleDB and QuestDB.

InfluxDB 3.0 vs Prometheus: which time-series database is better for metrics storage?▼

Comparing InfluxDB 3.0 and Prometheus for metrics storage depends on your ingestion needs and management preferences. This guidance provides a selection matrix to evaluate and choose the optimal TSDB for your specific metrics workload.

What high availability patterns are recommended for IoT time-series databases?▼

High availability patterns for IoT time-series databases ensure continuous storage and retrieval of time-stamped data. This guidance outlines architectural strategies for deploying resilient TSDBs tailored to IoT workloads.

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