How Can I Optimize Entity Framework for High-Volume Data Insertion?

Boosting Entity Framework's Data Insertion Speed

High-volume data insertion in Entity Framework demands optimized techniques. This article explores the most efficient methods to achieve rapid insertion speeds.

The Pitfall of Frequent SaveChanges() Calls

Calling SaveChanges() for each record is a major performance bottleneck. To maximize speed, avoid this practice. Consider these alternatives:

Batch SaveChanges():

• Execute a single SaveChanges() call to commit all insertions simultaneously.

Periodic SaveChanges():

• Process insertions in batches (e.g., 100 records) and call SaveChanges() after each batch.

Context Recycling:

• Dispose of the DbContext after each SaveChanges() and create a new one. This prevents the accumulation of tracked entities, which can significantly impact performance over time.

Illustrative Code:

This example showcases an efficient insertion strategy:

<code class="language-csharp">using (TransactionScope scope = new TransactionScope())
{
    MyDbContext context = null;
    try
    {
        context = new MyDbContext();
        context.Configuration.AutoDetectChangesEnabled = false;

        int count = 0;
        foreach (var entityToInsert in someCollectionOfEntitiesToInsert)
        {
            ++count;
            context = AddToContext(context, entityToInsert, count, 100, true);
        }

        context.SaveChanges();
    }
    finally
    {
        if (context != null)
            context.Dispose();
    }

    scope.Complete();
}</code>

Benchmark Results:

A test involving 560,000 entities yielded these results:

• Individual SaveChanges(): Several hours (extremely slow)
• Batching at 100 records: 164 seconds
• Batching at 1000 records: 191 seconds

These results indicate that periodic SaveChanges() with context disposal offers the best performance.

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