Are DynamoDB Updates strongly consistent?

Question

The whole reason why DynamoDB is fast and scalable is based on the fact that it is eventually consistent. But at the same time, it comes with this ConsistentRead option for operations like get, batchGet, and query which helps you make sure that the data you are reading is the latest one.

My question is about the update operation. First of all, it does not have the ConsistentRead option (one reason would be, update is not a read!). But at the same time, you can update a record in an atomic manner with ConditionExpression, like this:

await docClient.update({
    TableName: 'SomeTable',
    Key: {id},
    UpdateExpression: "set #status = :new_status",
    ConditionExpression: '#status = :old_status',
    ExpressionAttributeNames: {
        "#status": "status",
    },
    ExpressionAttributeValues: {
        ":old_status": "available",
        ":new_status": "done",
    },
}).promise()

This will make sure that at the time of update, the old value is available and if it isn't, the operation will fail with an exception thrown. So, in a sense, you can say that update is strongly consistent.

But my question is about a scenario in which you need to make sure the record exists. Let's say that you have one function which inserts a record. And another one that updates the same record (given its id). My concern is what if by the time the update operation is executed, because of eventually consistency of DynamoDB, there's no record matched and the update fails. As said before, the update operation does not come with a ConsistentRead option to make it strongly consistent.

Is this a valid concern? Is there anything I can do to help this?

Answer 1

There are no strongly consistent updates; strong consistency applies to reads where basically data viewed immediately after a write will be consistent for all observers of the entity.

When your application writes data to a DynamoDB table and receives an HTTP 200 response (OK), the write has occurred (in at least one storage location) and is durable. The data is eventually consistent across all storage locations, usually within one second or less. You can then choose to read this data in an eventually or strongly consistency fashion.

Concurrent writes to the same item should be handled with optimistic concurrency, you can do conditional writes using the DynamoDB Transaction Library (available in the AWS SDK for Java).

If you need to update more than one item atomically, you can use DynamoDB transactions.

DynamoDB transactions provide developers atomicity, consistency, isolation, and durability (ACID) across one or more tables within a single AWS account and region. You can use transactions when building applications that require coordinated inserts, deletes, or updates to multiple items as part of a single logical business operation.

https://aws.amazon.com/blogs/aws/new-amazon-dynamodb-transactions/

Alternatively, your use case may benefit from DynamoDB global tables which uses “last writer wins” reconciliation between concurrent writes.