Search engines are essential to building content-driven user experiences — from marketing websites to product catalogs to knowledge portals. But before you can deliver great search results, you need a solid content indexing strategy.
One of the foundational questions in search implementation is:
“How do we get our content into the search engine index?”
The answer revolves around two key paradigms: Push vs Pull indexing.
In this post, we’ll break down what each means, when to use them, real-world use cases, and how tools like ElasticSearch support both.
1. What is Search Indexing and Why Does It Matter?
Search indexing is the process of collecting, processing, and storing content in a search engine so it can be retrieved when users search.
Indexing ensures:
- New content is discoverable (e.g., product pages, articles)
- Updates are reflected in search (e.g., price or availability changes)
- Deleted content is removed from results
⚠️ Without proper indexing, your search results may be stale, incomplete, or misleading — leading to a poor user experience.
2. Push vs Pull Indexing: Core Concepts
Push Indexing
You actively send content to the search engine via APIs, SDKs, or data pipelines.
When to Use:
- Real-time updates are essential (e.g., stock, pricing)
- You own/control the source (e.g., CMS, PIM)
- Structured content (databases, JSON)
Typical Scenarios:
- E-commerce platforms updating inventory
- CMS pushing new articles
- News feeds or user-generated content systems
Pull Indexing
The search engine retrieves content itself using crawlers, connectors, or scheduled jobs.
When to Use:
- Indexing public or 3rd-party content
- Static content where real-time isn’t critical
- Unstructured sources (HTML, PDFs, docs)
Typical Scenarios:
- Crawling a blog using
sitemap.xml - Indexing SharePoint or Google Drive documents
- Pulling external data via REST APIs
3. Push vs Pull: Decision Matrix
4. ElasticSearch as an Example
Push Indexing in ElasticSearch
- Use Index API or Bulk API to send data
- Set up Ingest Pipelines for transformation
POST /products/_doc/123
{
"name": "Product X",
"description": "High quality...",
"price": 59.99
}Pull Indexing in ElasticSearch
Via Enterprise Search connectors:
- Web crawler (starting from sitemap)
- REST API data source
- Database connectors (MySQL, MongoDB, etc.)
5. Real-World Use Cases
6. How Other Platforms Handle Indexing
7. Final Thoughts: Designing Your Indexing Pipeline
When deciding between Push and Pull:
Consider:
- Content structure (structured vs unstructured)
- Frequency of updates
- Source system control
- Access restrictions
Hybrid approaches often work best:
- Push structured, frequently updated content (e.g., products)
- Pull public or slowly changing content (e.g., blogs, FAQs)
Takeaway
Before implementing search, take time to define your indexing strategy — it’s as important as search relevance itself.
If you’re using ElasticSearch:
- Start with Push for internal systems
- Explore Pull using crawlers or connectors as your content ecosystem expands
And remember: great search depends not just on what you show, but on how fast and reliably you get it there.