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Why is My Entity Framework Async Operation 10x Slower Than Synchronous?

Linda Hamilton
Release: 2025-01-10 18:51:41
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Why is My Entity Framework Async Operation 10x Slower Than Synchronous?

Entity Framework Async Performance Bottleneck

Problem:

Asynchronous Entity Framework database calls exhibit significantly slower performance than their synchronous counterparts, often experiencing a tenfold increase in execution time. Consider this example:

<code class="language-csharp">// Retrieve albums
var albums = await this.context.Albums
    .Where(x => x.Artist.ID == artist.ID)
    .ToListAsync();</code>
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Root Cause:

This performance issue stems from a flaw in EF 6's asynchronous implementation. When dealing with tables containing binary columns, EF incorrectly employs non-sequential data retrieval (CommandBehavior.Default) instead of the more efficient sequential access (CommandBehavior.SequentialAccess).

Analysis:

  1. Inefficient Data Retrieval: Non-sequential reads force the database to load the entire row into memory for each record, leading to substantial performance penalties, especially with large binary fields.
  2. Async Overhead: EF 6's asynchronous mechanisms introduce significant overhead through numerous background tasks and synchronization primitives. This overhead compounds the problem, particularly with large datasets.

Consequences:

  1. Performance Degradation: The tenfold slowdown highlights the severity of this performance issue.
  2. Resource Strain: The excessive task creation and synchronization consume considerable system resources, resulting in increased CPU and memory usage.

Resolution:

While future EF versions are expected to address this, a workaround involves manually wrapping the synchronous operation within an asynchronous method using TaskCompletionSource<T>. This bypasses EF's inefficient asynchronous implementation.

Summary:

The performance drop in asynchronous Entity Framework operations isn't inherent to asynchronous programming but a specific bug in EF 6's implementation. Employing a manual asynchronous wrapper effectively mitigates this performance bottleneck and improves application responsiveness.

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