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Indexing in Elasticsearch and MongoDB differ in the following ways:

1. Data Structure: Elasticsearch is a document-oriented search engine that stores data as JSON documents, whereas MongoDB is a document-oriented NoSQL database that stores data in BSON format.

2. Search Capabilities: Elasticsearch provides a powerful search engine with advanced search and aggregation functionalities, while MongoDB provides basic search capabilities.

3. Scalability: Elasticsearch is designed to be highly scalable, while MongoDB has some limitations when it comes to scaling horizontally.

4. Querying: Elasticsearch uses a query language based on Lucene, while MongoDB uses a query language similar to SQL.

5. Integration: Elasticsearch has built-in support for integrating with various data sources and tools, while MongoDB requires third-party connectors for integration with other data sources.

6. Performance: Elasticsearch is optimized for near real-time search and allows for very high-speed querying and indexing. MongoDB may be slower in comparison, especially for large datasets.