Efficient Web Services with Marten V4

We’re genuinely close to finally pulling the damn trigger on Marten V4. One of the last things I’m coding for the release is a new recipe for users to write very efficient web services backed by Marten database storage.

A Traditional .Net Approach

Before I get into the exact mechanics of that, let’s set the stage a little bit and draw some contrasts with a more traditional .Net web service stack. Let’s start by saying that in that traditional stack, you’re not using any kind of CQRS and the system state is persisted in the “one true model” approach using Entity Framework Core and an RDBMS like Sql Server. Now, in some web services you need to query data from the database and serve up a subset of that data into the outgoing HTTP response in a web service endpoint. The typical flow — with a focus on what’s happening under the covers — would be to:

  1. ASP.Net Core receives an HTTP GET, finds the proper endpoint, and calls the right handler for that route. Not that it actually matters, but let’s assume the endpoint handler is an MVC Core Controller method
  2. ASP.Net Core invokes a call to your DI container to build up the MVC controller object, and calls the right method for the route
  3. You’ve been to .Net conferences and internalized the idea that an MVC controller shouldn’t get too big or do things besides HTTP mediation, so you’re delegating to a tool like MediatR. MediatR itself is going to go through another DI container service resolution to find the right handler for the input model, then invoke that handler
  4. EF Core issues a query against your Sql Server database. If you’re needing to fetch data on more than just the root aggregate model, the query is going to be an outer join against all the child tables too
  5. EF Core loops around in the database rows and creates objects for your .Net domain model classes based on its ORM mappings
  6. You certainly don’t want to send the raw domain model on the wire because of coupling concerns, or don’t want every bit of data exposed to the client in a particular web service, so you use some kind of tool like AutoMapper to transform the internal domain model objects built up by EF Core into Data Transfer Objects (DTO) purposely designed to go over the wire.
  7. Lastly, you return the outgoing DTO model, which is serialized to JSON and sent down the HTTP response by MVC Core

Sound pretty common? That’s also a lot of overhead. A lot of memory allocations, data mappings between structures, JSON serialization, and a lot of dictionary lookups just to get data out of the database and spit it out into the HTTP response. It’s also a non-trivial amount of code, and I’d argue that some of the tools I mentioned are high ceremony.

Now do CQRS!

I initially thought of CQRS as looking like a whole lot more work to code, and that’s not an uncommon impression when folks are first introduced to it. I’ve come to realize over time that it’s not really more work so much as it’s really just doing about the same amount of work in different places and different times in the application’s workflow.

Now let’s at least introduce CQRS into our application architecture. I’m not saying that that automatically implies using event sourcing, but let’s say that you are writing a pre-built “read side” model of the state of your system directly to a database of some sort. Now from that same web service I was describing before, you just need to fetch that persisted “read side” model from the database and spit that state right out to the HTTP response.

Now then, I’ve just yada, yada’d all the complexity of the CQRS architecture that continuously updates the read side view for you, but hey, Marten does that for you too and that can be a shortly forthcoming follow up blog post.

Finally bringing Marten V4 into play, let’s say our read side model for an issue tracking system looks like this:

    public class Note
        public string UserName { get; set; }
        public DateTime Timestamp { get; set; }
        public string Text { get; set; }

    public class Issue
        public Guid Id { get; set; }
        public string Description { get; set; }
        public bool Open { get; set; }

        public IList<Note> Notes { get; set; }

Before anyone gets bent out of shape by this, it’s perfectly possible to tell Marten to serialize the persisted documents to JSON with camel or even snake casing to be more idiomatic JSON or Javascript friendly.

Now, let’s build out two controller endpoints, one that gives you an Issue payload by searching by its id, and a second endpoint that gives you all the open Issue models in a single JSON array payload. That controller — using some forthcoming functionality in a new Marten.AspNetCore Nuget — looks like this:

    public class GetIssueController: ControllerBase
        private readonly IQuerySession _session;

        public GetIssueController(IQuerySession session)
            _session = session;

        public Task Get(Guid issueId)
            // This "streams" the raw JSON to the HttpResponse
            // w/o ever having to read the full JSON string or
            // deserialize/serialize within the HTTP request
            return _session.Json
                .WriteById<Issue>(issueId, HttpContext);

        public Task OpenIssues()
            // This "streams" the raw JSON to the HttpResponse
            // w/o ever having to read the full JSON string or
            // deserialize/serialize within the HTTP request
            return _session.Query<Issue>()
                .Where(x => x.Open)

In the GET: /issue/{issueId} endpoint, you’ll notice the call to the new IQuerySession.Json.WriteById() extension method, and how I’m passing to it the current HttpContext. That method is:

  1. Executing a database query against the underlying Postgresql database. And in this case, all of the data is stored in a single column in a single row, so there’s not JOINs or sparse datasets like there would be with an ORM querying an object that has child collections.
  2. Write the raw bytes of the persisted JSON data directly to the HttpResponse.Body without ever bothering to write the whole thing to a .Net string and definitely without having to incur the overhead of JSON deserialization/serialization. That extension method also sets the HTTP content-length and content-type response headers, as well as setting the HTTP status code to 200 if the document is found, or 404 if the data is not found.

In the second HTTP endpoint for GET: /issue/open, the call to WriteArray(HttpContext) is doing something very similar, but writing the results as a JSON array.

By no means is this technique going to be applicable to every HTTP GET endpoint, but when it does, this is far, far more efficient and simpler to code than the more traditional approach that involves all the extra pieces and just has so much more memory allocations and hardware operations going on just to shoot some JSON down the wire.

For a little more context, here’s a test against the /issue/{issueId} endpoint, with a cameo from Alba to help me test the HTTP behavior:

        public async Task stream_a_single_document_hit()
            var issue = new Issue {Description = "It's bad", Open = true};

            var store = theHost.Services.GetRequiredService<IDocumentStore>();
            using (var session = store.LightweightSession())
                await session.SaveChangesAsync();

            var result = await theHost.Scenario(s =>

            var read = result.ReadAsJson<Issue>();


and one more test showing the “miss” behavior:

        public async Task stream_a_single_document_miss()
            await theHost.Scenario(s =>

Feedback anyone?

This code isn’t even released yet even in an RC Nuget, so feel very free to make any kind of suggestion or send us feedback.


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