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#Rename collection mongodb compass manual

Due to how Azure Cosmos DB handles replication, all writes are automatically majority quorum by default when using strong consistency.

Some applications rely on a Write Concern, which specifies the number of responses required during a write operation. However, it supports Azure role-based access control (Azure RBAC) and read-write and read-only passwords or keys that can be obtained through the connection string pane in the Azure portal.

User and role managementĪzure Cosmos DB doesn't yet support users and roles. TTL can be enabled for collections from the Azure portal. Time-to-live (TTL)Īzure Cosmos DB supports a time-to-live (TTL) based on the timestamp of the document. SessionsĪzure Cosmos DB doesn't yet support server-side sessions commands. You only need to specify the shard key while creating the containers or querying the data.

#Rename collection mongodb compass manual

Azure Cosmos DB doesn't support manual sharding commands, which means you don't have to invoke commands such as addShard, balancerStart, moveChunk etc. It manages shard creation, placement, and balancing automatically. ShardingĪzure Cosmos DB supports automatic, server-side sharding.

#Rename collection mongodb compass drivers

Client drivers must add retryWrites=false to their connection string. Retryable WritesĪzure Cosmos DB doesn't yet support retryable writes. Azure Cosmos DB doesn't support manual replication commands. This logic is extended out to achieve low-latency, global replication as well. ReplicationĪzure Cosmos DB supports automatic, native replication at the lowest layers. GridFSĪzure Cosmos DB supports GridFS through any GridFS-compatible MongoDB driver. The API for MongoDB supports various indexes to enable sorting on multiple fields, improve query performance, and enforce uniqueness. When you use the findOneAndUpdate operation, sort operations on a single field are supported, but sort operations on multiple fields aren't supported.

#Rename collection mongodb compass update

Update operators Field update operators Command For example, given the following original query: find(). When there's a need to include $ or |, it's best to create two (or more) regex queries. However, using 'i' modifier (case-insensitivity) and 'm' modifier (multiline) causes the collection scan in all expressions. In the $regex queries, left-anchored expressions allow index search. Indexes and index properties Indexes Command The API for MongoDB does not support comparison expressions with an array literal in the query. Database commandsĪzure Cosmos DB for MongoDB supports the following database commands: Query and write operation commands CommandĪggregation pipeline Aggregation commands Command Functions utilizing supported server commands are compatible with Azure Cosmos DB for MongoDB. Client-side wrapper functions such as deleteMany() and updateMany() internally utilize the delete() and update() server commands. In MongoDB, indexes are defined in the collection level and indexes on any field or subfield of the documents in a collection are supported.įor this tutorial, we’ll use the following data set to demonstrate the indexing functionality of MongoDB.This article only lists the supported server commands and excludes client-side wrapper functions. This ordering helps to perform equality matches and range-based query operations efficiently. These values are used to order the indexed fields. In simplest terms, indexes store the values of the indexed fields outside the table or collection and keep track of their location in the disk. Indexes are special data structures that store a small part of the Collection’s data in a way that can be queried easily. Use the right-hand menu to navigate.) What are indexes in MongoDB? (This article is part of our MongoDB Guide.

#Rename collection mongodb compass how to

In this tutorial, I’ll walk you through different types of indexes and show you how to create and manage indexes in MongoDB. By limiting the number of documents to be queried, you’ll increases the overall performance of the application.

Significantly slow down your applicationįortunately, using indexes fixes both these issues.

Result in various performance bottlenecks.

In MongoDB, querying without indexes is called a collection scan. When querying data without indexes, the query will have to search for all the records within a database to find data that match the query. Indexes provide users with an efficient way of querying data.

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