Federated search vs enterprise search: Key difference

Federated search	Enterprise search
Searches across distributed sources Leaves data in its original location and format Sends queries to multiple separate systems Results are gathered and combined at search time Better for frequently changing data May have higher latency due to real-time querying Maintains data sovereignty (each source keeps control)	Creates a central unified index Copies and normalizes all data into one repository Searches are performed against the unified index Results come from a single source Better for fast performance Requires ongoing synchronization with source systems Needs more storage for the central index

What do they have in common?

Both federated search and enterprise search tools share some key goals and characteristics. They both aim to give users a "single search box" experience and try to provide unified results by removing the need to search for information in multiple places manually. Both search solutions handle different types, from unstructured documents to structured databases to break down information and data silos. Their fundamental purpose of making information easily discoverable across multiple sources is the same.

Which one to choose?

While traditionally organizations had to weigh the tradeoffs between between federated search and enterprise search, modern solutions challenge this dichotomy. For instance, Qatalog has developed a federated search approach that addresses many traditional limitations by avoiding data indexing entirely, ensuring real-time results through direct API access, and solving permission and scalability challenges.

Understanding these different approaches and their use cases remains valuable for organizations evaluating their search needs:

Federated search is best for

• Searching across external systems you don't control

• Finding real-time information that changes frequently

• When data must stay in its source system for security or compliance

• When you need to search across partner or third-party systems

Common examples

• Libraries searching across multiple academic databases

• Travel sites searching multiple booking systems

• E-commerce aggregators searching multiple retailers

• Research portals searching multiple scientific databases

• Healthcare systems searching across different patient record systems

Enterprise search is best for

• Searching internal company content you control

• When fast search performance is crucial

• When you need advanced security and access controls

• When content changes less frequently

• When you want rich search features like faceting and filters

Common examples

• Company-wide search across internal documents and systems

• Knowledge management portals

• Customer service platforms searching support content

• Legal document management systems

• Corporate intranets

Combining federated and enterprise search in real-life

Many organizations start with enterprise search for their internal content and add federated search capabilities when they need to include external sources. For example, a company might use enterprise search for their internal documents but add federated search to include partner catalogs or external databases.

Let me explain the hybrid approach with a practical example:

A large healthcare organization might use:

Enterprise search for internal content, such as:

• Patient records from their database

• Internal policies and procedures

• Staff directories and documents

• Hospital equipment inventory

Federated search to bring in external or real-time information:

• Live insurance coverage checks

• Real-time bed availability from partner hospitals

• Clinical trial databases

• Drug interaction databases

• External medical research repositories

By combining both approaches, they get:

• Fast, comprehensive search of internal content through their central index (enterprise search)

• Real-time access to crucial external information that can't or shouldn't be copied to their systems (federated search)

• A single search interface for their staff to access everything

The key is to use each type of search for what it does best rather than trying to force everything into one approach.

Hybrid search tool

Modern AI search technologies continue to blur the line between enterprise and federated search. Let's look deeper at how Qatalog achieves this:

• It eliminates the need for data indexing, instead using direct API access to source systems. This means search results are always real-time, and no sensitive data is stored.
• It solves the common permission headache by inheriting security settings directly from source systems.
• It also addresses the scalability challenge. Without maintaining indexes, adding more data sources doesn't create the same infrastructure demands as traditional approaches.

This shows how modern federated search solutions can overcome traditional limitations like performance and security concerns while maintaining real-time access and data sovereignty benefits. It's a good example of how the technology has evolved beyond the traditional trade-offs between federated and enterprise search approaches.