Enterprise search vs. federated search: Which to choose?

What is enterprise search?

Enterprise search tools help employees quickly search through their organization's internal information. Unlike federated search, this approach crawls and indexes data from multiple sources within an organization and stores it in a central repository. When users search, the tool queries this central database rather than the original sources.

Common data sources that enterprise search tools index include company knowledge bases, intranets and document management systems.

What is federated search?

Federated search technology sends queries to multiple external data sources, such as websites, search engines and academic journals, to retrieve information. Unlike enterprise search, which indexes and stores content in a unified repository, federated search leaves the data at its source and aggregates the results.

Examples include academic search tools, such as WorldCat and EBSCO, and travel platforms that aggregate results from multiple hotel booking websites.

4 differences between enterprise and federated search

Enterprise search tools catalog and organize data in a central repository or index, whereas federated search pulls data from external systems. This leads to key differences, including data access and search speed.

1. Data access

Enterprise and federated search tools access data in different ways. Enterprise search tools catalog or crawl data from various internal sources, such as content management systems, SQL databases and CRM platforms, and store it in a unified index. The search engine then uses this central index when users make queries.

Federated systems, on the other hand, send user queries to multiple external sources, such as databases and cloud apps, in real time and aggregate the results in a list.

2. Search speed

Enterprise search tools only need to search their centralized index, which reduces latency and reliance on external systems. Federated search tools are typically slower than enterprise search engines because they must send queries to multiple external systems and wait for all responses before displaying results.

3. Search relevance

Enterprise search engines typically offer more relevant results than the federated approach because they gather information from across the organization into one system. They organize data in a structured way and often use AI to analyze the meaning behind the content.

Conversely, federated systems rely on each external source's own search capabilities and ranking algorithms. They lack a unified view of content across the different repositories and, therefore, cannot apply consistent metadata and relevancy scoring algorithms to the content. As a result, the system is more likely to return fragmented and unhelpful information.

4. Deployment complexity

Enterprise search tools require more upfront investment because they ingest, organize and index content, which requires IT teams to configure connectors and sync permissions. This approach also requires more storage capacity and processing power, in addition to regular maintenance to keep the index up to date.

Federated systems offer a simpler and less expensive implementation because they don't store and process data locally. Instead, they use APIs to connect to and retrieve data from external systems. While API usage fees can add up over time, this approach can be more cost-effective in the short term.

When should organizations use enterprise search?

Organizations typically use enterprise search to unify, organize and retrieve information from their own internal sources. Despite a more complex implementation, it offers a faster experience and more accurate results.

Enterprise search makes sense in the following situations:

• The organization wants to search its own internal data.
• The IT team has the resources for content indexing.
• Speed and relevancy are crucial.
• The organization wants to implement advanced, AI-powered search algorithms.

Common enterprise search use cases include consulting firms creating search tools to sift through their research reports, and manufacturers building knowledge bases to help engineers find technical product information.

When should organizations use federated search?

Despite enterprise search's advantages in speed and relevance, federated search remains the optimal approach in use cases that involve multisystem environments or strict data residency requirements.

Organizations might choose federated search in the following situations:

• Regulatory constraints require the data to remain in the original system.
• The company lacks the financial or technical resources for indexing.
• A third party owns the data.
• Different repositories require their own unique search algorithms.
• Data lives in systems that don't integrate well.

Examples of when an organization would use federated search include a hospital searching across patient records or a company unifying disparate apps after a merger.

Key takeaways

Enterprise search creates a centralized content index and offers speedy performance and highly relevant results. This approach works well for organizations with sufficient IT resources and many internal knowledge assets. Federated search queries data in its original location, which can save deployment costs yet sacrifices performance and relevance.

Many organizations use enterprise and federated search together. For instance, a law firm might use enterprise search for internal case documents and federated search to connect to court records databases. This hybrid approach offers the advantages of both methods.

Tim Murphy is site editor for Informa TechTarget's SearchCustomerExperience and SearchContentManagement sites.