Skip to main content

Understanding AsNoTrackingWithIdentityResolution in Entity Framework Core

When working with Entity Framework Core, understanding change tracking behavior is crucial for both performance and data consistency. While I was ware of the AsNoTracking() method, I discovered a lesser-known but powerful alternative: AsNoTrackingWithIdentityResolution() during a code review. 

Let's explore what makes this method special and when you should use it.

Quick recap: What is AsNoTracking()?

Before diving into AsNoTrackingWithIdentityResolution, let's briefly review AsNoTracking(). By default, EF Core tracks all entities returned from queries in the change tracker. This tracking enables:

  • Automatic detection of changes to entities
  • Update operations without explicitly attaching entities
  • Identity resolution (ensuring only one instance per entity exists in memory)

However, tracking comes with overhead. When you're performing read-only operations where you don't need to update data, AsNoTracking() improves performance by skipping the change tracker entirely.

The problem AsNoTracking() creates

While AsNoTracking() improves performance, it introduces a subtle but important issue: duplicate entity instances. Without the change tracker performing identity resolution, you can end up with multiple instances of the same entity in memory.

Consider this scenario:

If multiple orders belong to the same customer, you'll get separate Customer instances for each order, even though they represent the same database record. This means:

  • Increased memory usage
  • Potential confusion when comparing entities
  • Loss of referential integrity in your object graph

Enter AsNoTrackingWithIdentityResolution()

AsNoTrackingWithIdentityResolution() solves this problem by providing the best of both worlds:

  • No change tracking (performance benefit)
  • Identity resolution (ensuring single instances of entities)

When you use AsNoTrackingWithIdentityResolution(), EF Core:

  1. Executes the query without attaching entities to the change tracker
  2. Maintains a temporary identity map during query materialization
  3. Ensures that entities with the same key reference the same instance
  4. Discards the identity map after the query completes

This means you get identity resolution during the query execution without the ongoing overhead of change tracking.

If you find yourself using AsNoTrackingWithIdentityResolution() frequently, you can set it as the default tracking behavior:

When to use each method

Use Default Tracking when:

  • You need to update, delete, or track changes to entities
  • Working with small result sets where tracking overhead is negligible
  • You need automatic change detection

Use AsNoTracking when:

  • Performing read-only operations
  • You don't have navigation properties or related entities
  • Maximum performance is critical
  • Result sets don't contain duplicate entities

Use AsNoTrackingWithIdentityResolution when:

  • Performing read-only operations with includes/joins
  • You need referential integrity in your object graph
  • Working with queries that return the same entity multiple times
  • You want to compare entities by reference

More information

EntityFrameworkQueryableExtensions.AsNoTrackingWithIdentityResolution<TEntity> Method (Microsoft.EntityFrameworkCore) | Microsoft Learn

DbContextOptionsBuilder.UseQueryTrackingBehavior Method (Microsoft.EntityFrameworkCore) | Microsoft Learn

Labels:

Popular posts from this blog

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME         ...
Read more

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...
Read more

A complex system designed from scratch never works

A few years ago, I worked as an architect on a big mainframe rewrite. I still count it as one of my failures. Not because the technology was wrong, but because I couldn't convince the management team to simplify the approach. Years later, the organization is still struggling to get the new system up and running. I left the project at the time, because I couldn't put my name behind an approach that would take very long and cost a lot of money without a working system to show for it along the way. Gall’s Law That memory keeps coming back to me, because it's a textbook case of Gall's Law playing out in real life. Gall's Law , from John Gall's Systemantics , states it plainly: A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works, and it cannot be patched to make it work. You have to start over with a simple system that works. What does that mean in practice,...
Read more