Azure Cosmos DB: Build a .NET Framework or Core application using the Gremlin API

Azure Cosmos DB is Microsoft's globally distributed multi-model database service. You can quickly create and query document, key/value, and graph databases, all of which benefit from the global distribution and horizontal scale capabilities at the core of Azure Cosmos DB.

This quick start demonstrates how to create an Azure Cosmos DB Gremlin API account, database, and graph (container) using the Azure portal. You then build and run a console app built using the open-source driver Gremlin.Net.

Prerequisites

If you don't already have Visual Studio 2017 installed, you can download and use the free Visual Studio 2017 Community Edition. Make sure that you enable Azure development during the Visual Studio setup.

If you already have Visual Studio 2017 installed, make sure to be installed up to Visual Studio 2017 Update 3.

If you don't have an Azure subscription, create a free account before you begin.

Create a database account

  1. In a new browser window, sign in to the Azure portal.

  2. Click Create a resource > Databases > Azure Cosmos DB.

    Azure portal "Databases" pane

  3. In the Create Azure Cosmos DB Account page, enter the settings for the new Azure Cosmos DB account.

    Setting Value Description
    Subscription Your subscription Select the Azure subscription that you want to use for this Azure Cosmos DB account.
    Resource Group Create new

    Then enter the same unique name as provided in ID
    Select Create new. Then enter a new resource-group name for your account. For simplicity, use the same name as your ID.
    Account Name Enter a unique name Enter a unique name to identify your Azure Cosmos DB account. Because documents.azure.com is appended to the ID that you provide to create your URI, use a unique ID.

    The ID can use only lowercase letters, numbers, and the hyphen (-) character. It must be between 3 and 31 characters in length.
    API Gremlin (graph) The API determines the type of account to create. Azure Cosmos DB provides five APIs: Core(SQL) for document databases, Gremlin for graph databases, MongoDB for document databases, Azure Table, and Cassandra. Currently, you must create a separate account for each API.

    Select Gremlin (graph) because in this quickstart you are creating a table that works with the Gremlin API.

    Learn more about the Graph API.
    Location Select the region closest to your users Select a geographic location to host your Azure Cosmos DB account. Use the location that's closest to your users to give them the fastest access to the data.

    Select Review+Create. You can skip the Network and Tags section.

    The new account blade for Azure Cosmos DB

  4. The account creation takes a few minutes. Wait for the portal to display the Congratulations! Your Azure Cosmos DB account was created page.

    The Azure portal Notifications pane

Add a graph

You can now use the Data Explorer tool in the Azure portal to create a graph database.

  1. Click Data Explorer > New Graph.

    The Add Graph area is displayed on the far right, you may need to scroll right to see it.

    The Azure portal Data Explorer, Add Graph page

  2. In the Add graph page, enter the settings for the new graph.

    Setting Suggested value Description
    Database ID sample-database Enter sample-database as the name for the new database. Database names must be between 1 and 255 characters, and cannot contain / \ # ? or a trailing space.
    Graph ID sample-graph Enter sample-graph as the name for your new collection. Graph names have the same character requirements as database IDs.
    Storage Capacity Fixed (10 GB) Leave the default value of Fixed (10 GB). This value is the storage capacity of the database.
    Throughput 400 RUs Change the throughput to 400 request units per second (RU/s). If you want to reduce latency, you can scale up the throughput later.
  3. Once the form is filled out, click OK.

Clone the sample application

Now let's clone a Gremlin API app from GitHub, set the connection string, and run it. You'll see how easy it is to work with data programmatically.

  1. Open a command prompt, create a new folder named git-samples, then close the command prompt.

    md "C:\git-samples"
    
  2. Open a git terminal window, such as git bash, and use the cd command to change to the new folder to install the sample app.

    cd "C:\git-samples"
    
  3. Run the following command to clone the sample repository. This command creates a copy of the sample app on your computer.

    git clone https://github.com/Azure-Samples/azure-cosmos-db-graph-gremlindotnet-getting-started.git
    
  4. Then open Visual Studio and open the solution file.

  5. Restore the NuGet packages in the project. This should include the Gremlin.Net driver, as well as the Newtonsoft.Json package.

  6. You can also install the Gremlin.Net driver manually using the Nuget package manager, or the nuget command-line utility:

    nuget install Gremlin.Net
    

Review the code

This step is optional. If you're interested in learning how the database resources are created in the code, you can review the following snippets. Otherwise, you can skip ahead to Update your connection string.

The following snippets are all taken from the Program.cs file.

  • Set your connection parameters based on the account created above (Line 19):

    private static string hostname = "your-endpoint.gremlin.cosmosdb.azure.com";
    private static int port = 443;
    private static string authKey = "your-authentication-key";
    private static string database = "your-database";
    private static string collection = "your-graph-container";
    
  • The Gremlin commands to be executed are listed in a Dictionary (Line 26):

    private static Dictionary<string, string> gremlinQueries = new Dictionary<string, string>
    {
        { "Cleanup",        "g.V().drop()" },
        { "AddVertex 1",    "g.addV('person').property('id', 'thomas').property('firstName', 'Thomas').property('age', 44)" },
        { "AddVertex 2",    "g.addV('person').property('id', 'mary').property('firstName', 'Mary').property('lastName', 'Andersen').property('age', 39)" },
        { "AddVertex 3",    "g.addV('person').property('id', 'ben').property('firstName', 'Ben').property('lastName', 'Miller')" },
        { "AddVertex 4",    "g.addV('person').property('id', 'robin').property('firstName', 'Robin').property('lastName', 'Wakefield')" },
        { "AddEdge 1",      "g.V('thomas').addE('knows').to(g.V('mary'))" },
        { "AddEdge 2",      "g.V('thomas').addE('knows').to(g.V('ben'))" },
        { "AddEdge 3",      "g.V('ben').addE('knows').to(g.V('robin'))" },
        { "UpdateVertex",   "g.V('thomas').property('age', 44)" },
        { "CountVertices",  "g.V().count()" },
        { "Filter Range",   "g.V().hasLabel('person').has('age', gt(40))" },
        { "Project",        "g.V().hasLabel('person').values('firstName')" },
        { "Sort",           "g.V().hasLabel('person').order().by('firstName', decr)" },
        { "Traverse",       "g.V('thomas').out('knows').hasLabel('person')" },
        { "Traverse 2x",    "g.V('thomas').out('knows').hasLabel('person').out('knows').hasLabel('person')" },
        { "Loop",           "g.V('thomas').repeat(out()).until(has('id', 'robin')).path()" },
        { "DropEdge",       "g.V('thomas').outE('knows').where(inV().has('id', 'mary')).drop()" },
        { "CountEdges",     "g.E().count()" },
        { "DropVertex",     "g.V('thomas').drop()" },
    };
    
  • Create a GremlinServer connection object using the parameters provided above (Line 52):

    var gremlinServer = new GremlinServer(hostname, port, enableSsl: true, 
                                                    username: "/dbs/" + database + "/colls/" + collection, 
                                                    password: authKey);
    
  • Create a new GremlinClient object (Line 56):

    var gremlinClient = new GremlinClient(gremlinServer);
    
  • Execute each Gremlin query using the GremlinClient object with an async task (Line 63). This will read the Gremlin queries from the dictionary defined above (Line 26):

    var results = await gremlinClient.SubmitAsync<dynamic>(query.Value);
    
  • Retrieve the result and read the values, which are formatted as a dictionary, using the JsonSerializer class from Newtonsoft.Json:

    foreach (var result in results)
    {
        // The vertex results are formed as dictionaries with a nested dictionary for their properties
        string output = JsonConvert.SerializeObject(result);
        Console.WriteLine(String.Format("\tResult:\n\t{0}", output));
    }
    

Update your connection string

Now go back to the Azure portal to get your connection string information and copy it into the app.

  1. From the Azure portal, navigate to your graph database account. In the Overview tab, you can see two endpoints-

    .Net SDK URI - This value is used when you connect to the graph account by using Microsoft.Azure.Graphs library.

    Gremlin Endpoint - This value is used when you connect to the graph account by using Gremlin.Net library.

    Copy the endpoint

    To run this sample, copy the Gremlin Endpoint value, delete the port number at the end, that is the URI becomes https://<your cosmos db account name>.gremlin.cosmosdb.azure.com

  2. In Program.cs paste the value over your-endpoint in the hostname variable in line 19.

    "private static string hostname = "<your cosmos db account name>.gremlin.cosmosdb.azure.com";

    The endpoint value should now look like this:

    "private static string hostname = "testgraphacct.gremlin.cosmosdb.azure.com";

  3. Next, navigate to the Keys tab and copy PRIMARY KEY value from the portal, and paste it in the authkey variable, replacing the "your-authentication-key" placeholder in line 21.

    private static string authKey = "your-authentication-key";

  4. Using the information of the database created above, paste the database name inside of the database variable in line 22.

    private static string database = "your-database";

  5. Similarly, using the information of the container created above, paste the collection (which is also the graph name) inside of the collection variable in line 23.

    private static string collection = "your-collection-or-graph";

  6. Save the Program.cs file.

You've now updated your app with all the info it needs to communicate with Azure Cosmos DB.

Run the console app

Click CTRL + F5 to run the application. The application will print both the Gremlin query commands and results in the console.

The console window displays the vertexes and edges being added to the graph. When the script completes, press ENTER to close the console window.

Browse using the Data Explorer

You can now go back to Data Explorer in the Azure portal and browse and query your new graph data.

  1. In Data Explorer, the new database appears in the Graphs pane. Expand the database and container nodes, and then click Graph.

  2. Click the Apply Filter button to use the default query to view all the vertices in the graph. The data generated by the sample app is displayed in the Graphs pane.

    You can zoom in and out of the graph, you can expand the graph display space, add additional vertices, and move vertices on the display surface.

    View the graph in Data Explorer in the Azure portal

Review SLAs in the Azure portal

The throughput, storage, availability, latency, and consistency of the resources in your account are monitored in the Azure portal. Let's take a quick look at these metrics.

  1. Click Metrics in the navigation menu.

    Metrics in the Azure portal

  2. Click through each of the tabs so you're aware of the metrics Azure Cosmos DB provides.

    Each chart that's associated with the Azure Cosmos DB Service Level Agreements (SLAs) provides a line that shows if any of the SLAs have been violated. Azure Cosmos DB makes monitoring your SLAs transparent with this suite of metrics.

    Azure Cosmos DB metrics suite

Clean up resources

If you're not going to continue to use this app, delete all resources created by this quickstart with the following steps so you don't incur any charges:

  1. In the Azure portal, select Resource groups on the far left, and then select the resource group you created.

    If the left menu is collapsed, click Expand button to expand it.

    Metrics in the Azure portal

  2. In the new window select the resource group, and then click Delete resource group.

    Metrics in the Azure portal

  3. In the new window, type the name of the resource group to delete, and then click Delete.

Next steps

In this quickstart, you've learned how to create an Azure Cosmos DB account, create a graph using the Data Explorer, and run an app. You can now build more complex queries and implement powerful graph traversal logic using Gremlin.