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Delete Data in Bulk in Microsoft Dataverse Using C# and Web API

As Microsoft Dataverse environments grow, storage consumption becomes a significant concern. Large volumes of obsolete, test, duplicate, or imported records can impact performance, increase storage costs, and complicate data management.

Microsoft Dataverse provides a powerful Bulk Delete capability that allows administrators and developers to remove large sets of records asynchronously without blocking ongoing business operations. The bulk deletion process runs as a background job and supports scheduled execution, recurring jobs, email notifications, and failure tracking.

In this article, we'll explore:

  • What is Bulk Delete in Dataverse?

  • Real-world business scenario

  • C# implementation

  • Web API implementation

  • Advantages

  • Challenges

  • Best practices

  • Suggested screenshots

Screenshot 2026-08-08 230138

Why Bulk Delete?

According to Microsoft Learn, Bulk Delete helps organizations manage storage consumption and maintain data quality by removing:

  • Stale records

  • Invalid imported data

  • Test records

  • Data no longer relevant to business operations

Real-World Scenario

Imagine an insurance company maintaining customer interaction records in Dataverse.

Every day:

  • Thousands of temporary records are created.

  • Failed integration logs are stored.

  • Test records are generated by QA teams.

After six months:

  • Dataverse storage crosses 80%.

  • Environment performance starts degrading.

  • Storage costs increase.

The organization decides to automatically delete:

  • Test Accounts older than 90 days

  • Integration Logs older than 180 days

  • Temporary records older than 30 days

Instead of manually deleting records, a scheduled Bulk Delete Job performs cleanup automatically.

How Bulk Delete Works

A Bulk Delete operation creates a background job represented by the BulkDeleteOperation table in Dataverse. Microsoft records:

  • Total deleted records

  • Failed deletions

  • Schedule information

  • Recurrence details

If failures occur, details are stored in the BulkDeleteFailure table for troubleshooting.

Prerequisites

To execute Bulk Delete:

  • BulkDelete privilege

  • Delete privilege on target table

  • Read privilege on records being queried

System Administrators receive these permissions by default.

C# Example Using Dataverse SDK

Delete Inactive Accounts Older Than 1 Year

using Microsoft.Crm.Sdk.Messages;
using Microsoft.Xrm.Sdk.Query;

QueryExpression query = new QueryExpression("account");

query.Criteria.AddCondition(
    "modifiedon",
    ConditionOperator.OlderThanXMonths,
    12);

query.Criteria.AddCondition(
    "statecode",
    ConditionOperator.Equal,
    1);

BulkDeleteRequest request = new BulkDeleteRequest
{
    JobName = "Delete Old Inactive Accounts",
    QuerySet = new QueryExpression[]
    {
        query
    },
    StartDateTime = DateTime.UtcNow,
    RecurrencePattern = "",
    SendEmailNotification = false
};

BulkDeleteResponse response =
(BulkDeleteResponse)service.Execute(request);

Console.WriteLine($"Bulk Delete Job Created: {response.JobId}");

What Happens?

The system:

  1. Creates a background delete job.

  2. Runs asynchronously.

  3. Deletes matching records.

  4. Logs failures separately.

  5. Allows monitoring through system jobs.

Web API Example

Dataverse also supports a BulkDelete action via Web API.

POST https://yourorg.api.crm.dynamics.com/api/data/v9.2/BulkDelete
Content-Type: application/json

{
  "JobName": "Delete Old Accounts",
  "SendEmailNotification": false,
  "RecurrencePattern": "",
  "QuerySet": [
    {
      "@odata.type": "Microsoft.Dynamics.CRM.QueryExpression",
      "EntityName": "account"
    }
  ]
}

This creates a background deletion job that processes matching records asynchronously.

New Bulk Delete Options

Microsoft introduced additional controls for Bulk Delete processing.

Disable Recycle Bin

"Options": {
  "CanRecoverDeletedRecords": false
}

Benefit:

  • Faster deletion performance

  • Reduced recovery overhead

Trade-off:

  • Deleted records cannot be recovered.

Sandbox Fast Delete Mode

"Options": {
  "RunJobForSandbox": true
}

Benefit:

  • Much higher deletion throughput

Behavior:

  • Bypasses plugins

  • Bypasses workflows

  • Bypasses recycle bin

Supported only in Sandbox environments.

Monitoring Bulk Delete Jobs

Administrators can monitor:

  • Job status

  • Success count

  • Failure count

  • Execution time

from:

Advanced Settings → System Jobs → Bulk Delete Jobs

If records fail to delete, error information is captured in BulkDeleteFailure records.

Advantages of Bulk Delete

1. Reduces Dataverse Storage Cost

Removing obsolete records helps control database growth.

2. Improves Performance

Smaller datasets typically result in:

  • Faster searches

  • Faster views

  • Better reporting experience

3. Runs Asynchronously

Users can continue working while deletion occurs in the background.

4. Supports Scheduling

Jobs can run:

  • Daily

  • Weekly

  • Monthly

  • On-demand

5. Failure Tracking

Failed deletions are logged for troubleshooting.

Challenges and Considerations

Challenge 1: Cascading Deletes

Deleting parent records may remove related child records depending on Dataverse relationship settings.

Recommendation

Always review relationship behavior before execution.

Challenge 2: Plugin Execution

Bulk Delete triggers registered plugins and workflows during record deletion.

Recommendation

Assess business impact before deleting millions of records.

Challenge 3: No Rollback

If a Bulk Delete job partially succeeds and then fails, deleted records are not restored automatically.

Recommendation

Export critical data before running large jobs.

Challenge 4: Production Risks

Accidental query mistakes can delete critical business data.

Recommendation

Test query conditions in Sandbox first.

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