LinkedIn, the professional networking platform with over 810 million users worldwide, utilizes its own internal search engine to power searches on its site and mobile apps. While LinkedIn provides robust search capabilities customized for professional networking, there are some key factors to understand about what search engine LinkedIn uses and how it differs from broader web search engines like Google.
LinkedIn’s Internal Search Engine
LinkedIn uses its own proprietary search engine that is designed specifically for discovering people, jobs, companies, groups, and other professional content on LinkedIn. This internal search engine is not powered by external search providers like Google or Bing. LinkedIn engineered its customized search engine to take advantage of its unique data set of professional profiles, job listings, and other business-oriented content.
LinkedIn’s search functionality is focused on enabling users to find relevant professional connections, job opportunities, and business information. Some of the key features of LinkedIn’s internal search include:
- Searching by name, company, job title, school, and other profile attributes
- Location-based searching for finding professionals and jobs in specific cities or regions
- Search alerts for getting notifications on new matching profiles or jobs
- Advanced filters for narrowing search criteria to precisely tailor results
- Search history for revisiting past searches and results
LinkedIn prioritizes results that are in a user’s extended network and tailored to their own profile and previous activity. This helps surface more relevant connections compared to a standard web search.
Integration With Microsoft Bing
While LinkedIn’s primary search runs on its own search engine, it does have some integration with Microsoft’s Bing search engine. LinkedIn was acquired by Microsoft in 2016, so there has been some cross-pollination between the two companies’ products and technologies.
One way this integration manifests is that searches conducted on LinkedIn will also display a selection of supplementary results from Bing and Microsoft News if they are relevant to the query. However, LinkedIn results still take priority, with Bing/News results acting as supplemental content. The core search functionality remains LinkedIn’s own proprietary engine.
LinkedIn members can also optionally enable Bing as the default search engine when searching the broader web from LinkedIn’s toolbar. Without this configuration change enabled, Google remains the default. So Bing powers web searches if manually configured, but not LinkedIn site searches.
Why LinkedIn Doesn’t Rely on Google
With Google being the dominant search engine for general web searches, some may wonder why LinkedIn doesn’t just use Google for its searches. There are some key reasons why LinkedIn opted to build its own search capabilities:
- Customization for professional content – Google is designed to index the broader web, not just content within a single site. LinkedIn’s search is customized to deeply understand users, jobs, companies, groups, and other professional data.
- Control over rankings & relevancy – LinkedIn can tune its algorithms to surface the most relevant people and job results for searches without relying on external signals like Google’s PageRank.
- Search experience consistency – By controlling its search engine, LinkedIn can provide a more seamless experience across web and mobile apps and iterate quickly rather than relying on a third-party provider.
- User data privacy – Operating its own search provides LinkedIn more control over user data and prevents sharing search data externally.
In summary, LinkedIn prioritized building a comprehensive internal search engine tailored to professional networking so it could better serve its members’ needs and control the experience rather than outsourcing search to Google.
LinkedIn’s Search Architecture
Under the hood, LinkedIn’s search architecture consists of several key components powering its robust indexing and querying capabilities:
- Crawler – Crawls LinkedIn pages and profiles to index information.
- Document Processing Pipeline – Extracts key metadata from profiles.
- Query Engine – Handles search requests and queries the indexed data.
- Index – Billions of indexed documents and metadata to search against.
- Ranking Models – Algorithms that score results by relevance.
- Presentation Layer – Formats and displays the results page.
This simplified architecture outlines the core search components. In practice, LinkedIn operates a massively scalable search infrastructure across thousands of servers to handle over 3.5 billion member profile searches per day.
Key LinkedIn Search Infrastructure Components
| Component | Description |
|---|---|
| Crawler | Spider that discovers and fetches pages/profiles to index |
| Document Processing Pipeline | Extracts metadata like skills, employer, etc. to enrich indexed profiles |
| Query Engine | Handles search requests and queries the index |
| Index | Billions of indexed profiles, jobs, companies, etc. |
| Ranking Models | Algorithms that score results by relevance |
| Presentation Layer | Formats and displays the search results page |
Optimizing these components to keep pace with LinkedIn’s growth at scale presents significant technical challenges. But by investing heavily in search infrastructure, LinkedIn empowers its members to effectively tap into its unmatched professional data set.
Differences From Web Search Engines
While the basics of crawling, indexing, and querying underpin both LinkedIn and general web search engines like Google, there are some key differences in how LinkedIn search is optimized for its use cases:
- Focused data set – LinkedIn only indexes professional profile data, job listings, companies, and groups rather than the entire web.
- Custom data extraction – The document processing pipeline is tailored to LinkedIn’s member profile attributes.
- Priority on people – Keyword searches are structured to prioritize matching people over generic web pages.
- Professional relevancy – Ranking models factor in professional network connections more heavily.
- Custom features – Advanced filters, alerts, and other custom features catered for professional use cases.
While Google and LinkedIn both aim to serve users the most relevant results, LinkedIn’s technology stack and algorithms are optimized specifically for professional networking search queries.
Conclusion
In summary, LinkedIn relies on its own internal, custom search engine tailored to professional networking rather than outsourcing to an external provider. By building and controlling its search technology, LinkedIn can craft a search experience that deeply understands professional profiles, relationships, and roles. While LinkedIn does integrate some supplemental results from Microsoft Bing, its core search is powered by proprietary infrastructure purpose-built to help professionals discover relevant connections, jobs, content, and insights.
