What are the best indexing strategies for NoSQL databases?

What are the best indexing strategies for NoSQL databases?

The best indexing strategies for NoSQL databases often depend on the specific database type. For example, in document stores like MongoDB, using compound indexes can significantly improve query performance. In key-value stores, maintaining a sorted order can help with range queries.

Can you explain how secondary indexes work in NoSQL?

Secondary indexes in NoSQL databases allow you to query data based on fields that are not the primary key. They create a separate data structure that maps the indexed field to the primary key, enabling faster lookups.

What are the trade-offs of using indexes in NoSQL?

Using indexes can speed up read operations but may slow down write operations due to the overhead of maintaining the index. Additionally, indexes consume extra storage space.

Are there any specific NoSQL databases that handle indexing better than others?

Yes, databases like Cassandra and Elasticsearch are known for their efficient indexing capabilities. Cassandra uses a partitioning strategy that optimizes read and write performance, while Elasticsearch is built around a powerful indexing engine for full-text search.