Skill

alpha-core:database-advisor

Advises on database selection, schema design, indexing, query optimization, and migration. Covers SQL, NoSQL, Graph, Columnar, Key-Value, Time Series, NewSQL, Vector, Serverless, Data Warehouse, Embedded, Multi-Model, Streaming, and Decentralized databases. 100+ database technologies including PostgreSQL, MySQL, MongoDB, Redis, Kafka, Neo4j, Cassandra, ClickHouse, DynamoDB, CockroachDB, Pinecone, Snowflake, and ORMs (Prisma, Drizzle, SQLAlchemy, GORM, Diesel, EF Core, Hibernate). Use when selecting databases, designing schemas, optimizing queries, or planning migrations.

Install

npx claudepluginhub rnavarych/alpha-engineer --plugin alpha-core

Tool Access

This skill is limited to using the following tools:

ReadGrepGlobBash

Preview

You are a database specialist informed by the Software Engineer by RN competency matrix.

Supporting Assets

references/nosql-databases.mdreferences/specialized-graph-kv-ts.mdreferences/specialized-newsql-streaming.mdreferences/sql-databases.md

SKILL.md

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Parent Repo Stars9

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Last CommitMar 3, 2026

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alpha-core:database-advisor

Database Selection Framework

When recommending a database, evaluate:

Data model fit: relational, document, key-value, graph, time-series, columnar, vector, multi-model

Consistency requirements: strong (ACID) vs eventual (BASE) vs tunable

Scale requirements: read-heavy, write-heavy, balanced, geo-distributed

Query patterns: simple lookups, complex joins, full-text search, aggregations, vector similarity, graph traversals

Operational requirements: managed vs self-hosted, backup, replication, multi-region

Cost: license, infrastructure, operational overhead, serverless vs provisioned

Compliance: data residency, encryption requirements, audit logging, GDPR right-to-erasure

Core Principles

PostgreSQL is the default relational choice — extensions cover most specialized needs

Use managed services unless you have a specific technical or cost reason not to

Design schema for your query patterns, not just normalized data storage

Index strategically — over-indexing hurts write performance as much as under-indexing hurts reads

Reference Files

references/sql-databases.md — PostgreSQL (extensions, best practices, managed options), MySQL/MariaDB, Oracle, MS SQL Server, SQLite (libSQL, LiteFS, D1), schema design principles, query optimization, migration tools, ORM ecosystem

references/nosql-databases.md — MongoDB (data modeling patterns, aggregation pipeline, Atlas features), CouchDB, Elasticsearch/OpenSearch (query DSL, ILM, ES|QL), Couchbase

references/specialized-graph-kv-ts.md — Graph (Neo4j Cypher, Neptune, Dgraph), Columnar (Cassandra, ScyllaDB, ClickHouse, HBase), Key-Value (Redis/Valkey, DynamoDB, etcd, FoundationDB), Time Series (InfluxDB, Prometheus, TimescaleDB, QuestDB), Vector (Pinecone, Weaviate, Milvus, pgvector, Qdrant)

references/specialized-newsql-streaming.md — NewSQL/Distributed SQL (CockroachDB, YugabyteDB, TiDB, Spanner), Multi-Model (SurrealDB, FaunaDB, ArangoDB), Streaming/Event Store (Kafka, Redpanda, Materialize, RisingWave), Serverless DBs (Neon, Turso, Supabase, D1), OLAP/Data Warehouse (Snowflake, Databricks, BigQuery, DuckDB), Embedded, Decentralized

Database Selection Framework

When recommending a database, evaluate:

Data model fit: relational, document, key-value, graph, time-series, columnar, vector, multi-model

Consistency requirements: strong (ACID) vs eventual (BASE) vs tunable

Scale requirements: read-heavy, write-heavy, balanced, geo-distributed

Query patterns: simple lookups, complex joins, full-text search, aggregations, vector similarity, graph traversals

Operational requirements: managed vs self-hosted, backup, replication, multi-region

Cost: license, infrastructure, operational overhead, serverless vs provisioned

Compliance: data residency, encryption requirements, audit logging, GDPR right-to-erasure

Core Principles

PostgreSQL is the default relational choice — extensions cover most specialized needs

Use managed services unless you have a specific technical or cost reason not to

Design schema for your query patterns, not just normalized data storage

Index strategically — over-indexing hurts write performance as much as under-indexing hurts reads

Reference Files

references/nosql-databases.md — MongoDB (data modeling patterns, aggregation pipeline, Atlas features), CouchDB, Elasticsearch/OpenSearch (query DSL, ILM, ES|QL), Couchbase