Indexing strategy for Cosmos DB

In Azure Cosmos DB, indexing policies are crucial for optimizing query performance and managing costs. Each container in Cosmos DB has an indexing policy that dictates how its items are indexed. Here are the key aspects of how indexing policies work and how to design an efficient indexing strategy:

1. Default Indexing Policy: By default, Cosmos DB indexes every property of every item, which allows for maximum query flexibility. This is beneficial for general use but may not be optimal for all scenarios.
2. Indexing Modes: There are two main indexing modes in Cosmos DB:
   • Consistent: The index is updated synchronously as items are created, updated, or deleted. This ensures that read queries reflect the latest data.
   • None: Indexing is disabled, which can improve performance for bulk operations or when the container is used as a key-value store without the need for secondary indexes.
3. Customizing Indexing Policies: You can customize a container's indexing policy by including or excluding specific property paths. This allows you to optimize for specific workloads:
   • Exclude Properties: If certain properties are not queried, you can exclude them from indexing to reduce storage and write costs.
   • Index Specific Properties: You can choose to index only the properties that are frequently queried, which can enhance write performance and lower storage costs.
4. Vector Indexing: For scenarios involving high-cardinality data, vector indexing can improve query performance and reduce costs. This is particularly useful for applications like recommendation engines or semantic search.
5. Tuple Indexing: This allows you to define composite indexes on multiple properties, which can optimize queries that filter on those properties.

To design an efficient indexing strategy, consider the following:

• Analyze your query patterns to determine which properties are frequently accessed.
• Use the default indexing policy for general use but customize it based on specific application needs.
• Monitor performance and adjust indexing policies as your application evolves.

By carefully managing your indexing policies, you can achieve better performance and cost efficiency in Azure Cosmos DB.

References:

• Sample indexing policies in Cosmos DB (in Azure and Fabric)
• Indexing policies in Cosmos DB (in Azure and Fabric)
• Manage indexing policies in Azure Cosmos DB
• Indexing policies in Azure Cosmos DB
• Vector indexes
• Tuple indexing policy examples

Hi HimanshuSinha,
It looks like you're looking to understand how indexing policies work in Azure Cosmos DB and how to design an efficient indexing strategy. Here’s a rundown of what you need to know:

Understanding Indexing Policies

1. Default Behavior: Azure Cosmos DB automatically indexes every property of items in your container without requiring you to configure secondary indexes. The indexing policy defines how data is indexed and what properties are included.
   • Range Indexes: Used for numeric and string fields.
   • Spatial Indexes: Used for geographic data.
2. Reviewing Your Indexing Policy: To check or modify your indexing policy:
   • Open the Azure portal and navigate to your Cosmos DB account.
   • In the Data Explorer, select the database and container you're interested in.
   • Under Settings, select Indexing Policy to see current configurations.

Designing an Efficient Indexing Strategy

• Include Key Properties: Ensure that your queries filter on properties that are part of your indexing policy. If you often query using lastname, then ensure it's indexed.
• Secondary Indexes: If necessary, you can create secondary indexes for frequently queried columns that might not be indexed by default.

  
    CREATE INDEX ON sampleks.t1 (lastname);
  
  

• Composite Indexes: For complex queries that filter by multiple fields, consider creating composite indexes. This can optimize performance for queries involving both lastname and firstname.

  
    CREATE INDEX ON sampleks.t1 (lastname, firstname);
  
  

• Partition and Clustering Keys: Make sure to structure your queries around the partition key for better performance. Index both the partition and any frequently queried clustering keys.
• Minimize Over-indexing: Avoid indexing fields that change often or those which are rarely queried, as excessive indexing can slow down write operations.
• Using ALLOW FILTERING: As a temporary measure, if necessary, you can append ALLOW FILTERING to your queries to bypass indexing limitations, but this is not recommended for production environments due to potential performance degradation.

Best Practices for Indexing

• Regular Monitoring: Utilize Azure Monitor for Cosmos DB to keep an eye on your indexing performance, RU consumption, and latency.
• Iterative Optimization: Continuously refine your indexing strategy based on observed query performance metrics. Adjust indexes according to usage patterns.

Helpful Links

• Indexing in Azure Cosmos DB - Overview
• Manage Indexing Policies
• Troubleshoot query issues in Azure Cosmos DB

I hope this helps you get started on designing an effective indexing strategy in Azure Cosmos DB! If you have any more questions, feel free to ask.