Document Search Workload

read heavy

Summary

Full-text search with faceted aggregations over a document corpus. Read-heavy with asynchronous write indexing. Latency-sensitive for queries; accepts index staleness of 1–30 seconds. Search relevance and facet correctness are the primary quality dimensions.

Example Systems

·E-commerce product search with facets (category, price, brand)
·Documentation and knowledge base search
·Email and file search within enterprise applications
·Log search and analysis (Kibana over Elasticsearch)
·Job listing search with multi-attribute filtering
·Legal document search with full-text and metadata filters

Characteristics

CategorySEARCH

Read / write patternread heavy

Latency requirementlow

Consistency requirementeventual

Durability requiredNo

Ordering requiredNo

Capacity

Typical RPS2,000

Peak RPS20,000

Typical data volume50 GB

Growth rate2-20 GB/month; depends on document creation rate and index size factor

Seasonal spikes: E-commerce spikes during promotional events and sale periods; log search spikes during incidents when engineers search logs simultaneously (10× multiplier)

Access Patterns

full text searchaggregate

Recommended Patterns

cache asidewrite ahead log cdcread replica

Patterns to Avoid

two phase commit

Basis

Standard search workload with well-understood characteristics; Elasticsearch and Solr operational patterns are extensively documented

Used In Architecture Scenarios

Content Management Platformmoderate

Read-Heavy Application

A CMS for publishing and serving structured content: articles, documentation, product pages, and localized variants: where read APIs serve 50–100x more traffic than editorial write APIs. PostgreSQL stores the content graph (articles, authors, categories, taxonomy) and workflow state (draft, in-review, scheduled, published). Redis caches published content objects for read APIs. Elasticsearch powers full-text content search with faceting and relevance ranking. Cache invalidation on publish must be fast and complete; N+1 query patterns on content relationship traversal are the dominant database performance risk during reads.