index.md

title	summary	component	reviewed	redirects	related
NServiceBus DataBus feature	How to handle messages that are too large to be sent by a transport natively by using NServiceBus DataBus	DataBus	2024-08-01	nservicebus/databus samples/pipeline/stream-properties	samples/databus/file-share-databus samples/databus/custom-serializer samples/databus/blob-storage-databus samples/databus/redis

Although messaging systems work best with small message sizes, some scenarios require sending binary large objects (blobs) data along with a message (also known as a Claim Check). For this purpose, NServiceBus has a DataBus feature to overcome the message size limitations imposed by the underlying transport.

partial: obsolete

How it works

Instead of serializing the payload along with the rest of the message, the DataBus approach involves storing the payload in a separate location that both the sending and receiving parties can access, then putting the reference to that location in the message.

If the location is not available upon sending, the send operation will fail. When a message is received and the payload location is not available, the receive operation will fail too, resulting in the standard NServiceBus retry behavior, possibly resulting in the message being moved to the error queue if the error could not be resolved.

Transport message size limits

The DataBus may be used to send messages which exceed the transport's message size limit, which is determined by the message size limit of the underlying queuing/storage technologies.

Note

Not all transports have message size limits and some technologies, such as Azure Service Bus, have increased over time. Current message size limits are stated in the documentation linked in the table below.

Transport	Maximum size
Amazon SQS	256KB
Amazon SQS (using S3)	2GB
Azure Storage Queues	64KB
Azure Service Bus (Standard tier)	256KB
Azure Service Bus (Premium tier)	100MB
RabbitMQ	Configured by max_message_size
SQL Server	No limit
Learning	No limit
MSMQ	4MB

Enabling the DataBus

See the individual DataBus implementations for details on enabling and configuring the DataBus.

• File Share Data Bus
• Azure Blob Storage Data Bus

Cleanup

By default, blobs are stored with no set expiration. If messages have a time to be received set, the DataBus will pass this along to the data bus storage implementation.

Note

The value used should be aligned with the ServiceControl audit retention period if it is required that DataBus blob keys in messages sent to the audit queue can still be fetched.

Specifying DataBus properties

There are two ways to specify the message properties to be sent using the DataBus:

1. Using the ClaimCheckProperty<T> type
2. Message conventions

Note

DataBus properties must be top-level properties on a message class.

Using ClaimCheckProperty<T>

Set the type of the property to be sent over as ClaimCheckProperty<byte[]>:

snippet: MessageWithLargePayload

Using message conventions

NServiceBus also supports defining DataBus properties by convention. This allows data properties to be sent using the DataBus without using ClaimCheckProperty<T>, thus removing the need for having a dependency on NServiceBus from the message types.

In the configuration of the endpoint include:

snippet: DefineMessageWithLargePayloadUsingConvention

Set the type of the property as byte[]:

snippet: MessageWithLargePayloadUsingConvention

partial: serialization

DataBus attachments cleanup

The DataBus implementations each behave differently when cleaning up the physical attachments used to transfer the data properties.

Why attachments are not removed by default

Automatically removing these attachments can cause problems in many situations. For example:

• The supported implementations do not participate in distributed transactions. If the message handler throws an exception and the transaction rolls back, the delete operation on the attachment cannot be rolled back. Therefore, when the message is retried, the attachment will no longer be present, causing additional problems.
• The message can be deferred so that the file will be processed later. Removing the file after deferring the message, results in a message without the corresponding file.
• Functional requirements might dictate the message to be available for a longer duration.
• If the DataBus feature is used when publishing an event to multiple subscribers, neither the publisher nor any specific subscribing endpoint can determine when all subscribers have successfully processed the message, allowing the file to be cleaned up.
• If message processing fails, it will be handled by the recoverability feature. This message can then be retried some period after that failure. The attachment files need to exist for that message to be re-processed correctly.

Alternatives

Note

A combination of these techniques may be used.

• Use a different transport or different tier (e.g. Azure Service Bus Premium instead of Standard).
• Use message body compression, which works well on text-based payloads like XML and JSON or any payload (text or binary) that contains repetitive data.
  • The message mutator sample demonstrates message body compression.
• Use a more efficient serializer, such as a binary serializer.
  • A custom serializer can usually be implemented in only a few lines of code.
  • Some binary serializers are maintained by the community.
• Use NServiceBus.Attachments for unbounded binary payloads. The package is similar to the DataBus, but has some differences:
  • Read on demand: Attachments are only retrieved when read by a consumer.
  • Async enumeration: The package supports processing all data items using an IAsyncEnumerable.
  • No serialization: The serializer is not used, which may result in a significant reduction in memory usage.
  • Direct stream access: This makes the package more suitable for binary large objects (blobs since stream contents do not necessarily have to be loaded into memory before storing them or when retrieving them.

Other considerations

Monitoring and reliability

The storage location for DataBus blobs is critical to the operation of endpoints. As such, it should be as reliable as other infrastructure, such as the transport or persistence. It should also be monitored for errors and be actively maintained. Since messages cannot be sent or received when the storage location is unavailable, it may be necessary to stop endpoints when maintenance tasks occur.

Auditing

The data stored in DataBus blobs may be considered part of an audit record. In these cases, the blobs should be archived alongside messages for as long as the audit record is required.