Develop solutions that use Azure Cosmos DB Cheatsheets

By Saeed Salehi

4 min read


Key benefits of multi-master replication protocol:

  • Unlimited elastic write and read scalability.
  • 99.999% read and write availability all around the world.
  • Guaranteed reads and writes served in less than 10 milliseconds at the 99th percentile.

Elements in an Azure Cosmos account

Azure Cosmos account is the fundamental unit of global distribution and high availability (has unique DNS name)

maximum of 50 Azure Cosmos accounts under an Azure subscription

hierarchy of different entities in an Azure Cosmos DB account:

  • Database Account
    • Database
      • Container (Collection, Table, Graph, ...)
        • Stored Procedure
        • User-defined functions
        • triggers
        • conflicts
        • merge procedures
        • items (document, row, node, edge, ...)

Azure Cosmos containers

container is a schema-agnostic container of items A container is horizontally partitioned and then replicated across multiple regions

Throughput modes:

  • Dedicated provisioned throughput mode: exclusively reserved for that container and it is backed by the SLAs.
  • Shared provisioned throughput mode: share the provisioned throughput with the other containers in the same database (shared among all the “shared throughput” containers)

Azure Cosmos Items

Depending on which API representation can be different:

Cosmos entitySQL APICassandra APIAzure Cosmos DB API for MongoDBGremlin APITable API
Azure Cosmos itemItemRowDocumentNode or edgeItem

consistency levels

consistency levels are region-agnostic and are guaranteed for all operations

consistency models:

  • strong: guarantees that reads get the most recent version of an item
  • bounded staleness: guarantees that a read hax a max lag (either version or time)
  • session: guarantees that a client session will read its own writes
  • consistent prefix: guarantees that updates are returned in order
  • eventual: no guarantees for order

Strong and Bounded staleness will consume twice the normal RU for a request

Consider the following points if your application is built using SQL API or Table API:

  • For many real-world scenarios, session consistency is optimal and it's the recommended option.
  • If you need stricter consistency: bounded staleness consistency level.
  • If you need less strict consistency: consistent prefix consistency level.
  • If you need the highest throughput and the lowest latency,: eventual consistency level.
  • If you need even higher data durability: custom consistency level at the application layer.

Consistency guarantees:

  • When the consistency level is set to bounded staleness, Cosmos DB guarantees that the clients always read the value of a previous write, with a lag bounded by the staleness window.

  • When the consistency level is set too strong, the staleness window is equivalent to zero, and the clients are guaranteed to read the latest committed value of the write operation.

  • For the remaining three consistency levels, the staleness window is largely dependent on your workload , if there are no write operations on the database, a read operation with eventual, session, or consistent prefix consistency levels is likely to yield the same results as a read operation with strong consistency level

Probabilistically Bounded Staleness (PBS) metric

This metric provides an insight into how often you can get a stronger consistency than the consistency level that you've currently configured on your Azure Cosmos account

supported APIs


Stores data in document format.

Querying items using the Structured Query Language (SQL)


This API stores data in a document structure, via BSON format.

It is compatible with MongoDB wire protocol; however, it does not use any native MongoDB related code

Cassandra API

This API stores data in column-oriented schema. Cassandra API is wire protocol compatible with the Apache Cassandra.

Cassandra Query Language (CQL)

Gremlin API

Graph queries and stores data as edges and vertices

Currently only supports OLTP scenarios.

Table API

stores data in key/value format Table API only supports OLTP scenarios.

az cosmosdb create \
    --resource-group $resourceGroupName \
    --name $accountName \
    --locations regionName=$location
    --capabilities EnableTable

C# Implementation

TableServiceClientThis client class provides a client-side logical representation for the Azure Cosmos DB service. The client object is used to configure and execute requests against the service.
TableClientThis client class is a reference to a table that may, or may not, exist in the service yet. The table is validated server-side when you attempt to access it or perform an operation against it.
ITableEntityThis interface is the base interface for any items that are created in the table or queried from the table. This interface includes all required properties for items in the API for Table.
TableEntityThis class is a generic implementation of the ITableEntity interface as a dictionary of key-value pairs.

Request Units (RU)

you pay for the throughput you provision and the storage you consume on an hourly basis

fetching a single item by its ID and partition key value, for a 1KB item is 1RU

  • Provisioned throughput mode:provision the number of RUs for your application on a per-second basis in increments of 100 RUs per second.
  • Serverless mode: In this mode, you don't have to provision any throughput
  • Autoscale mode: suited for mission-critical workloads that have variable or unpredictable traffic patterns

partitioning in Azure Cosmos DB

Logical Partition

A logical partition consists of a set of items that have the same partition key.

A logical partition also defines the scope of database transactions

Physical partitions

Physical partitions are collections of logical partitions physical partitions are an internal implementation of the system and they are entirely managed by Azure Cosmos DB

  • The number of throughput provisioned (10,000 RU/s limit for physical)
  • Total data storage (up to 50GB data).

Hot partitions lead to inefficient use of provisioned throughput (many requests directed to a small subset of partitions)

partition key

Once you select your partition key, it is not possible to change it in-place Components:

  • The partition key path (for example: "/userId")
  • The partition key value (for example: "Saeed")

Partition key should:

  • property that has a value which does not change
  • Have a high cardinality
  • Spread request unit (RU) consumption and data storage evenly across all logical partitions

read-heavy containers

For large read-heavy containers you might want to choose a partition key that appears frequently as a filter in your queries.

synthetic partition key

  • Concatenate multiple properties of an item
  • Use a partition key with a random suffix
  • Use a partition key with pre-calculated suffixes

Microsoft .NET SDK v3 for Azure Cosmos DB


CosmosClient client = new CosmosClient(endpoint, key);

Create a database

// An object containing relevant information about the response
DatabaseResponse databaseResponse = await client.CreateDatabaseIfNotExistsAsync(databaseId, 10000);

Read a database by ID

DatabaseResponse readResponse = await database.ReadAsync();

Delete a database

await database.DeleteAsync();

Create a container

// Set throughput to the minimum value of 400 RU/s
ContainerResponse simpleContainer = await database.CreateContainerIfNotExistsAsync(
    id: containerId,
    partitionKeyPath: partitionKey,
    throughput: 400);

Get a container by ID

Container container = database.GetContainer(containerId);
ContainerProperties containerProperties = await container.ReadContainerAsync();

Delete a container

await database.GetContainer(containerId).DeleteContainerAsync();

Create an item (JSON serializable)

ItemResponse<SalesOrder> response = await container.CreateItemAsync(salesOrder, new PartitionKey(salesOrder.AccountNumber));

Read an item

string id = "[id]";
string accountNumber = "[partition-key]";
ItemResponse<SalesOrder> response = await container.ReadItemAsync(id, new PartitionKey(accountNumber));

Query an item

QueryDefinition query = new QueryDefinition(
    "select * from sales s where s.AccountNumber = @AccountInput ")
    .WithParameter("@AccountInput", "Account1");

FeedIterator<SalesOrder> resultSet = container.GetItemQueryIterator<SalesOrder>(
    requestOptions: new QueryRequestOptions()
        PartitionKey = new PartitionKey("Account1"),
        MaxItemCount = 1

Create resources by Azure CLI

Create the Azure Cosmos DB account

az cosmosdb create --name <myCosmosDBacct> --resource-group az204-cosmos-rg

Retrieve the primary key for the account

az cosmosdb keys list --name <myCosmosDBacct> --resource-group az204-cosmos-rg

stored procedures

The context object provides access to all operations that can be performed in Azure Cosmos DB, and access to the request and response object

input parameters are always sent as a string to the stored procedure

Stored procedures have a limited amount of time to run on the server.

All collection functions return a Boolean value that represents whether that operation will complete or not

triggers and user-defined functions

pre-triggers and post-triggers Triggers are not automatically executed, they must be specified for each database operation where you want them to execute

Pre-triggers cannot have any input parameters

The post-trigger runs as part of the same transaction for the underlying item itself an exception during the post-trigger execution will fail the whole transaction. Anything committed will be rolled back and an exception returned.

var context = getContext()
var container = context.getCollection()
var response = context.getResponse()

//rest of the code