The product needs it now
- 01Large content libraries or catalogs
- 02E-commerce product search
- 03User-generated content discovery
- 04Multi-criteria filtering needed
High-value capability
Search Functionality
Full-text search, filtering, and faceted search for product catalogs, content, and user data.
3-7 daysTypical timeline
$1,000 - $3,000Typical range
4Approaches compared
SCOPE DECISION
Does this belong
in the first release?
A capability is only essential when the product promise depends on it. Use these signals to keep the decision tied to user value.
The release works without it
- 01Small datasets (<100 items)
- 02Simple list filtering is sufficient
- 03No discovery use case
IMPLEMENTATION OPTIONS
Choose the approach
that fits the product.
The right technology depends on ownership, scale, integration depth, and how much operational responsibility the team wants to carry.
PostgreSQL Full-Text SearchBuilt-in search capabilities in PostgreSQL
Strengths
- No extra service
- Good for simple search
- Transactional consistency
- Limited relevance tuning
- Slower at scale
- Basic features
AlgoliaHosted search-as-a-service
Strengths
- Instant search
- Excellent relevance
- Great UI libraries
- Easy setup
- Expensive at scale
- Data sync required
- Vendor lock-in
MeilisearchOpen-source, fast search engine
Strengths
- Self-hostable
- Very fast
- Good typo tolerance
- Simple API
- Smaller ecosystem
- Manual hosting/scaling
ElasticsearchEnterprise-grade search engine
Strengths
- Extremely powerful
- Scalable
- Rich analytics
- Complex to operate
- Resource-intensive
- Overkill for MVPs
DELIVERY SEQUENCE
A practical path
through the work.
- 01Define search requirements (speed, relevance, facets)
- 02Choose search technology based on scale
- 03Design search index schema
- 04Implement data sync/indexing pipeline
- 05Build search API endpoint
- 06Create search UI with instant results
- 07Add filters and faceted navigation
- 08Implement search analytics
WATCH FOR
Common implementation mistakes.
- 01Not handling empty/no results states
- 02Missing typo tolerance
- 03Poor relevance ranking
- 04Not syncing index with database
- 05Missing search suggestions
- 06Ignoring search analytics
QUESTIONS
Before you commit the scope.
When should I upgrade from PostgreSQL search?+
When you need instant search (<100ms), typo tolerance, faceted filtering, or have 10k+ searchable items. Start with PostgreSQL, migrate when needed.
How do I keep search index in sync?+
Use database webhooks/triggers or event-driven updates. For MVPs, near-real-time sync (few seconds delay) is usually acceptable.
Should I build autocomplete?+
Yes for discovery-focused products. Autocomplete improves UX significantly. Use search-as-you-type with debouncing (200-300ms).
DISCUSS YOUR APP
Turn this decision
into working software.
Bring the product context and current scope. We will choose the approach after the release is clear.
Discuss your app