How to use Azure Table storage from Node.js


The content in this article applies to the original Azure Table storage. However, there is now a premium offering for table storage, the Azure Cosmos DB Table API that offers throughput-optimized tables, global distribution, and automatic secondary indexes. To learn more and try out the premium experience, please check out Azure Cosmos DB Table API.


This topic shows how to perform common scenarios using the Azure Table service in a Node.js application.

The code examples in this topic assume you already have a Node.js application. For information about how to create a Node.js application in Azure, see any of these topics:

What is Table storage

Azure Table storage stores large amounts of structured data. The service is a NoSQL datastore which accepts authenticated calls from inside and outside the Azure cloud. Azure tables are ideal for storing structured, non-relational data. Common uses of Table storage include:

  • Storing TBs of structured data capable of serving web scale applications
  • Storing datasets that don't require complex joins, foreign keys, or stored procedures and can be denormalized for fast access
  • Quickly querying data using a clustered index
  • Accessing data using the OData protocol and LINQ queries with WCF Data Service .NET Libraries

You can use Table storage to store and query huge sets of structured, non-relational data, and your tables will scale as demand increases.

Table storage concepts

Table storage contains the following components:

Tables storage component diagram

  • URL format: Code addresses tables in an account using this address format:
    http://<storage account><table>

    You can address Azure tables directly using this address with the OData protocol. For more information, see

  • Storage Account: All access to Azure Storage is done through a storage account. See Azure Storage Scalability and Performance Targets for details about storage account capacity.
  • Table: A table is a collection of entities. Tables don't enforce a schema on entities, which means a single table can contain entities that have different sets of properties. The number of tables that a storage account can contain is limited only by the storage account capacity limit.
  • Entity: An entity is a set of properties, similar to a database row. An entity can be up to 1MB in size.
  • Properties: A property is a name-value pair. Each entity can include up to 252 properties to store data. Each entity also has three system properties that specify a partition key, a row key, and a timestamp. Entities with the same partition key can be queried more quickly, and inserted/updated in atomic operations. An entity's row key is its unique identifier within a partition.

For details about naming tables and properties, see Understanding the Table Service Data Model.

Create an Azure storage account

The easiest way to create your first Azure storage account is by using the Azure portal. To learn more, see Create a storage account.

You can also create an Azure storage account by using Azure PowerShell, Azure CLI, or the Storage Resource Provider Client Library for .NET.

If you prefer not to create a storage account at this time, you can also use the Azure storage emulator to run and test your code in a local environment. For more information, see Use the Azure Storage Emulator for Development and Testing.

Configure your application to access Azure Storage

To use Azure Storage, you need the Azure Storage SDK for Node.js, which includes a set of convenience libraries that communicate with the storage REST services.

Use Node Package Manager (NPM) to install the package

  1. Use a command-line interface such as PowerShell (Windows), Terminal (Mac), or Bash (Unix), and navigate to the folder where you created your application.
  2. Type npm install azure-storage in the command window. Output from the command is similar to the following example.

    azure-storage@0.5.0 node_modules\azure-storage
    +-- extend@1.2.1
    +-- xmlbuilder@0.4.3
    +-- mime@1.2.11
    +-- node-uuid@1.4.3
    +-- validator@3.22.2
    +-- underscore@1.4.4
    +-- readable-stream@1.0.33 (string_decoder@0.10.31, isarray@0.0.1, inherits@2.0.1, core-util-is@1.0.1)
    +-- xml2js@0.2.7 (sax@0.5.2)
    +-- request@2.57.0 (caseless@0.10.0, aws-sign2@0.5.0, forever-agent@0.6.1, stringstream@0.0.4, oauth-sign@0.8.0, tunnel-agent@0.4.1, isstream@0.1.2, json-stringify-safe@5.0.1, bl@0.9.4, combined-stream@1.0.5, qs@3.1.0, mime-types@2.0.14, form-data@0.2.0, http-signature@0.11.0, tough-cookie@2.0.0, hawk@2.3.1, har-validator@1.8.0)
  3. You can manually run the ls command to verify that a node_modules folder was created. Inside that folder you will find the azure-storage package, which contains the libraries you need to access storage.

Import the package

Add the following code to the top of the server.js file in your application:

var azure = require('azure-storage');

Set up an Azure Storage connection

The azure module will read the environment variables AZURE_STORAGE_ACCOUNT and AZURE_STORAGE_ACCESS_KEY, or AZURE_STORAGE_CONNECTION_STRING for information required to connect to your Azure storage account. If these environment variables are not set, you must specify the account information when calling TableService.

Create a table

The following code creates a TableService object and uses it to create a new table. Add the following near the top of server.js.

var tableSvc = azure.createTableService();

The call to createTableIfNotExists will create a new table with the specified name if it does not already exist. The following example creates a new table named 'mytable' if it does not already exist:

tableSvc.createTableIfNotExists('mytable', function(error, result, response){
    // Table exists or created

The result.created will be true if a new table is created, and false if the table already exists. The response will contain information about the request.


Optional filtering operations can be applied to operations performed using TableService. Filtering operations can include logging, automatically retrying, etc. Filters are objects that implement a method with the signature:

function handle (requestOptions, next)

After doing its preprocessing on the request options, the method needs to call "next", passing a callback with the following signature:

function (returnObject, finalCallback, next)

In this callback, and after processing the returnObject (the response from the request to the server), the callback needs to either invoke next if it exists to continue processing other filters or simply invoke finalCallback otherwise to end the service invocation.

Two filters that implement retry logic are included with the Azure SDK for Node.js, ExponentialRetryPolicyFilter and LinearRetryPolicyFilter. The following creates a TableService object that uses the ExponentialRetryPolicyFilter:

var retryOperations = new azure.ExponentialRetryPolicyFilter();
var tableSvc = azure.createTableService().withFilter(retryOperations);

Add an entity to a table

To add an entity, first create an object that defines your entity properties. All entities must contain a PartitionKey and RowKey, which are unique identifiers for the entity.

  • PartitionKey - determines the partition that the entity is stored in
  • RowKey - uniquely identifies the entity within the partition

Both PartitionKey and RowKey must be string values. For more information, see Understanding the Table Service Data Model.

The following is an example of defining an entity. Note that dueDate is defined as a type of Edm.DateTime. Specifying the type is optional, and types will be inferred if not specified.

var task = {
  PartitionKey: {'_':'hometasks'},
  RowKey: {'_': '1'},
  description: {'_':'take out the trash'},
  dueDate: {'_':new Date(2015, 6, 20), '$':'Edm.DateTime'}


There is also a Timestamp field for each record, which is set by Azure when an entity is inserted or updated.

You can also use the entityGenerator to create entities. The following example creates the same task entity using the entityGenerator.

var entGen = azure.TableUtilities.entityGenerator;
var task = {
  PartitionKey: entGen.String('hometasks'),
  RowKey: entGen.String('1'),
  description: entGen.String('take out the trash'),
  dueDate: entGen.DateTime(new Date(Date.UTC(2015, 6, 20))),

To add an entity to your table, pass the entity object to the insertEntity method.

tableSvc.insertEntity('mytable',task, function (error, result, response) {
    // Entity inserted

If the operation is successful, result will contain the ETag of the inserted record and response will contain information about the operation.

Example response:

{ '.metadata': { etag: 'W/"datetime\'2015-02-25T01%3A22%3A22.5Z\'"' } }


By default, insertEntity does not return the inserted entity as part of the response information. If you plan on performing other operations on this entity, or wish to cache the information, it can be useful to have it returned as part of the result. You can do this by enabling echoContent as follows:

tableSvc.insertEntity('mytable', task, {echoContent: true}, function (error, result, response) {...}

Update an entity

There are multiple methods available to update an existing entity:

  • replaceEntity - updates an existing entity by replacing it
  • mergeEntity - updates an existing entity by merging new property values into the existing entity
  • insertOrReplaceEntity - updates an existing entity by replacing it. If no entity exists, a new one will be inserted
  • insertOrMergeEntity - updates an existing entity by merging new property values into the existing. If no entity exists, a new one will be inserted

The following example demonstrates updating an entity using replaceEntity:

tableSvc.replaceEntity('mytable', updatedTask, function(error, result, response){
  if(!error) {
    // Entity updated


By default, updating an entity does not check to see if the data being updated has previously been modified by another process. To support concurrent updates:

  1. Get the ETag of the object being updated. This is returned as part of the response for any entity-related operation and can be retrieved through response['.metadata'].etag.
  2. When performing an update operation on an entity, add the ETag information previously retrieved to the new entity. For example:

    entity2['.metadata'].etag = currentEtag;

  3. Perform the update operation. If the entity has been modified since you retrieved the ETag value, such as another instance of your application, an error will be returned stating that the update condition specified in the request was not satisfied.

With replaceEntity and mergeEntity, if the entity that is being updated doesn't exist, then the update operation will fail. Therefore if you wish to store an entity regardless of whether it already exists, use insertOrReplaceEntity or insertOrMergeEntity.

The result for successful update operations will contain the Etag of the updated entity.

Work with groups of entities

Sometimes it makes sense to submit multiple operations together in a batch to ensure atomic processing by the server. To accomplish that, use the TableBatch class to create a batch, and then use the executeBatch method of TableService to perform the batched operations.

The following example demonstrates submitting two entities in a batch:

var task1 = {
  PartitionKey: {'_':'hometasks'},
  RowKey: {'_': '1'},
  description: {'_':'Take out the trash'},
  dueDate: {'_':new Date(2015, 6, 20)}
var task2 = {
  PartitionKey: {'_':'hometasks'},
  RowKey: {'_': '2'},
  description: {'_':'Wash the dishes'},
  dueDate: {'_':new Date(2015, 6, 20)}

var batch = new azure.TableBatch();

batch.insertEntity(task1, {echoContent: true});
batch.insertEntity(task2, {echoContent: true});

tableSvc.executeBatch('mytable', batch, function (error, result, response) {
  if(!error) {
    // Batch completed

For successful batch operations, result will contain information for each operation in the batch.

Work with batched operations

Operations added to a batch can be inspected by viewing the operations property. You can also use the following methods to work with operations:

  • clear - clears all operations from a batch
  • getOperations - gets an operation from the batch
  • hasOperations - returns true if the batch contains operations
  • removeOperations - removes an operation
  • size - returns the number of operations in the batch

Retrieve an entity by key

To return a specific entity based on the PartitionKey and RowKey, use the retrieveEntity method.

tableSvc.retrieveEntity('mytable', 'hometasks', '1', function(error, result, response){
    // result contains the entity

Once this operation is complete, result will contain the entity.

Query a set of entities

To query a table, use the TableQuery object to build up a query expression using the following clauses:

  • select - the fields to be returned from the query
  • where - the where clause

    • and - an and where condition
    • or - an or where condition
  • top - the number of items to fetch

The following example builds a query that will return the top five items with a PartitionKey of 'hometasks'.

var query = new azure.TableQuery()
  .where('PartitionKey eq ?', 'hometasks');

Since select is not used, all fields will be returned. To perform the query against a table, use queryEntities. The following example uses this query to return entities from 'mytable'.

tableSvc.queryEntities('mytable',query, null, function(error, result, response) {
  if(!error) {
    // query was successful

If successful, result.entries will contain an array of entities that match the query. If the query was unable to return all entities, result.continuationToken will be non-null and can be used as the third parameter of queryEntities to retrieve more results. For the initial query, use null for the third parameter.

Query a subset of entity properties

A query to a table can retrieve just a few fields from an entity. This reduces bandwidth and can improve query performance, especially for large entities. Use the select clause and pass the names of the fields to be returned. For example, the following query will return only the description and dueDate fields.

var query = new azure.TableQuery()
  .select(['description', 'dueDate'])
  .where('PartitionKey eq ?', 'hometasks');

Delete an entity

You can delete an entity using its partition and row keys. In this example, the task1 object contains the RowKey and PartitionKey values of the entity to be deleted. Then the object is passed to the deleteEntity method.

var task = {
  PartitionKey: {'_':'hometasks'},
  RowKey: {'_': '1'}

tableSvc.deleteEntity('mytable', task, function(error, response){
  if(!error) {
    // Entity deleted


Consider using ETags when deleting items, to ensure that the item hasn't been modified by another process. See Update an entity for information on using ETags.

Delete a table

The following code deletes a table from a storage account.

tableSvc.deleteTable('mytable', function(error, response){
        // Table deleted

If you are uncertain whether the table exists, use deleteTableIfExists.

Use continuation tokens

When you are querying tables for large amounts of results, look for continuation tokens. There may be large amounts of data available for your query that you might not realize if you do not build to recognize when a continuation token is present.

The results object returned during querying entities sets a continuationToken property when such a token is present. You can then use this when performing a query to continue to move across the partition and table entities.

When querying, a continuationToken parameter may be provided between the query object instance and the callback function:

var nextContinuationToken = null;
    function (error, results) {
        if (error) throw error;

        // iterate through results.entries with results

        if (results.continuationToken) {
            nextContinuationToken = results.continuationToken;


If you inspect the continuationToken object, you will find properties such as nextPartitionKey, nextRowKey and targetLocation, which can be used to iterate through all the results.

There is also a continuation sample within the Azure Storage Node.js repo on GitHub. Look for examples/samples/continuationsample.js.

Work with shared access signatures

Shared access signatures (SAS) are a secure way to provide granular access to tables without providing your storage account name or keys. SAS are often used to provide limited access to your data, such as allowing a mobile app to query records.

A trusted application such as a cloud-based service generates a SAS using the generateSharedAccessSignature of the TableService, and provides it to an untrusted or semi-trusted application such as a mobile app. The SAS is generated using a policy, which describes the start and end dates during which the SAS is valid, as well as the access level granted to the SAS holder.

The following example generates a new shared access policy that will allow the SAS holder to query ('r') the table, and expires 100 minutes after the time it is created.

var startDate = new Date();
var expiryDate = new Date(startDate);
expiryDate.setMinutes(startDate.getMinutes() + 100);
startDate.setMinutes(startDate.getMinutes() - 100);

var sharedAccessPolicy = {
  AccessPolicy: {
    Permissions: azure.TableUtilities.SharedAccessPermissions.QUERY,
    Start: startDate,
    Expiry: expiryDate

var tableSAS = tableSvc.generateSharedAccessSignature('mytable', sharedAccessPolicy);
var host =;

Note that the host information must be provided also, as it is required when the SAS holder attempts to access the table.

The client application then uses the SAS with TableServiceWithSAS to perform operations against the table. The following example connects to the table and performs a query.

var sharedTableService = azure.createTableServiceWithSas(host, tableSAS);
var query = azure.TableQuery()
  .where('PartitionKey eq ?', 'hometasks');

sharedTableService.queryEntities(query, null, function(error, result, response) {
  if(!error) {
    // result contains the entities

Since the SAS was generated with only query access, if an attempt were made to insert, update, or delete entities, an error would be returned.

Access Control Lists

You can also use an Access Control List (ACL) to set the access policy for a SAS. This is useful if you wish to allow multiple clients to access the table, but provide different access policies for each client.

An ACL is implemented using an array of access policies, with an ID associated with each policy. The following example defines two policies, one for 'user1' and one for 'user2':

var sharedAccessPolicy = {
  user1: {
    Permissions: azure.TableUtilities.SharedAccessPermissions.QUERY,
    Start: startDate,
    Expiry: expiryDate
  user2: {
    Permissions: azure.TableUtilities.SharedAccessPermissions.ADD,
    Start: startDate,
    Expiry: expiryDate

The following example gets the current ACL for the hometasks table, and then adds the new policies using setTableAcl. This approach allows:

var extend = require('extend');
tableSvc.getTableAcl('hometasks', function(error, result, response) {
    var newSignedIdentifiers = extend(true, result.signedIdentifiers, sharedAccessPolicy);
    tableSvc.setTableAcl('hometasks', newSignedIdentifiers, function(error, result, response){
        // ACL set

Once the ACL has been set, you can then create a SAS based on the ID for a policy. The following example creates a new SAS for 'user2':

tableSAS = tableSvc.generateSharedAccessSignature('hometasks', { Id: 'user2' });

Next steps

For more information, see the following resources.