Strata

Manage multi-tier data with a unified Go API for Get, Set, Delete, and Search.

Updated Feb 28, 2026

Search Tags:#caching #postgresql #redis #go #vector search #distributed ledger #data library

Ready to run

npx skills add https://github.com/AndrewDonelson/Strata --skill strata

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Strata
Source: https://github.com/AndrewDonelson/Strata/tree/main
Command: npx skills add https://github.com/AndrewDonelson/Strata --skill strata

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables AI coding agents to interact with the Strata Go library, simplifying complex data management tasks by providing a unified API over multiple caching and persistence layers.

Core Features & Use Cases

Multi-Tier Caching: Seamlessly utilizes L1 (memory), L2 (Redis), and L3 (PostgreSQL) for efficient data retrieval and storage.
Optional L4 Sync: Integrates with a distributed ledger for immutable audit trails and cross-node consistency.
Use Case: Imagine managing user profiles in a high-traffic application. Strata automatically handles caching, ensures data consistency across instances, and provides optional auditability via its L4 layer, allowing developers to focus on business logic rather than boilerplate data operations.

Quick Start

Use the Strata skill to initialize a new data store with provided PostgreSQL and Redis connection details.

Frequently Asked Questions about Strata

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

FAQPage Schema

How do I manage multi-tier caching across memory, Redis, and PostgreSQL in Go?▼

Multi-tier caching in Go is managed by defining data schemas once and interacting via a unified API for Get, Set, Delete, and Search operations across L1 (memory), L2 (Redis), and L3 (PostgreSQL). This handles automatic caching and cache invalidation.

What is the best way to add an immutable audit trail to a Go caching architecture?▼

Adding an immutable audit trail to a caching architecture uses an optional L4 distributed ledger tier. This enables cross-node consistency and provides an immutable audit trail alongside the standard memory and database layers.

Can I perform vector search in PostgreSQL using a Go data library?▼

Vector search in PostgreSQL is supported via pgvector integration. The data library includes optional vector search capabilities, allowing you to perform similarity searches directly through the unified API.

How do I handle write propagation and transactions across multiple data tiers?▼

Write propagation and transactions across multiple data tiers are handled automatically by the unified API. The library manages automatic write propagation, cache invalidation, and supports transactions across the memory, Redis, and PostgreSQL layers.

Does the Strata data library require separate schemas for caching and persistence?▼

The Strata data library does not require separate schemas for caching and persistence. Developers define data schemas once, and the unified API handles interactions and automatic synchronization across all configured data tiers.

What data security and observability features are included in a multi-tier Go data library?▼

Data security and observability features in this multi-tier architecture include built-in encryption and observability. These features operate alongside automatic schema migration to ensure secure and monitored data operations.