Non-relational database query best practices

Help teams design maintainable, secure, and performant MongoDB and non-relational database queries for Java applications.

What is covered in this Skill?

• Document modeling for aggregates, embedded documents, references, arrays, and bounded growth
• MongoDB JSON Schema validation and compatibility-aware schema evolution
• Query design: explicit predicates, projections, sort stability, pagination, collation, and read concerns
• Index strategy: compound indexes, covering queries, partial indexes, TTL indexes, unique constraints, and lifecycle review
• Aggregation pipelines: stage ordering, $match pushdown, $project, $lookup, $unwind, $group, and memory controls
• Consistency, transactions, idempotency, migration safety, testing, observability, and production diagnostics

Scope: Framework-agnostic MongoDB and non-relational data modeling. For Java framework integrations, defer to the matching Spring Boot, Quarkus, or Micronaut MongoDB skill.

Constraints

Keep recommendations at the database-modeling and query layer unless the user explicitly asks for Java framework integration. After editing this repository's XML sources, regenerate skills and verify the build.

• MANDATORY: Run ./mvnw compile or mvn compile before proposing Java or Maven changes in the same change set
• INJECTION: Never concatenate untrusted input into query documents, aggregation stages, JSON strings, JavaScript expressions, or $where; use driver/framework query builders and validated parameters
• SCHEMA: Prefer explicit document contracts, bounded arrays, stable identifiers, and validation rules over unconstrained document growth
• PERFORMANCE: Review explain() plans, scanned/returned ratios, sort coverage, and index selectivity before claiming a query is optimized
• FRAMEWORK: Defer Spring MongoDB to @315-frameworks-spring-mongodb, Quarkus MongoDB to @415-frameworks-quarkus-mongodb, Micronaut MongoDB to @515-frameworks-micronaut-mongodb, and Mongock migrations to the matching framework migration skill
• VERIFY: Run ./mvnw clean verify or mvn clean verify before promoting changes
• EDGE CASE: If the target database, version, shard topology, read/write concern, data volume, or latency requirement is missing and affects the recommendation, ask a clarifying question before editing queries or schemas
• EDGE CASE: If requested changes conflict with data safety, backwards compatibility, zero-downtime deployment, or retention requirements, explain the trade-off and ask for confirmation

When to use this skill

• Design MongoDB document schemas
• Review MongoDB queries and indexes
• Improve aggregation pipeline performance
• Model non-relational data access patterns
• Review NoSQL consistency and transaction trade-offs

Workflow

1. Read reference and assess data context

Read references/705-technologies-nosql-mongodb.md and inspect current collections, schemas, indexes, queries, aggregation pipelines, tests, and database configuration before proposing changes.

2. Identify workload and operational constraints

Confirm query patterns, cardinality, data volume, document growth, consistency requirements, shard topology, and migration constraints that shape the non-relational design.

3. Apply database-aligned changes

Implement or refactor database artifacts following the reference patterns and project conventions, keeping Java framework integration out of scope unless explicitly requested.

4. Run verification and report results

Execute appropriate build, schema validation, query-plan, migration, and test checks; summarize what changed, what was verified, and any remaining database risks.

Reference

For detailed guidance, examples, and constraints, see references/705-technologies-nosql-mongodb.md.