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Amazon DynamoDB mock implementation

Project description

ddbmock – a DynamoDB mock implementation.


DynamoDB is a minimalistic NoSQL engine provided by Amazon as a part of their AWS product.

DynamoDB allows you to store documents composed of unicode, number or binary data as well are sets. Each tables must define a hash_key and may define a range_key. All other fields are optional.

DynamoDB is really awesome but is terribly slooooow with managment tasks. This makes it completly unusable in test environements.

ddbmock brings a nice, tiny, in-memory or sqlite implementation of DynamoDB along with much better and detailed error messages. Among its niceties, it features a double entry point:

  • regular network based entry-point with 1:1 correspondance with stock DynamoDB

  • embeded entry-point with seamless boto intergration 1, ideal to avoid spinning yet another server.

ddbmock is not intended for production use. It will lose your data. you’ve been warned! I currently recommend the “boto extension” mode for unit-tests and the “server” mode for functional tests.


$ pip install ddbmock


$ hg clone ssh://
$ pip install nose nosexcover coverage mock webtest boto
$ python develop
$ nosetests # --no-skip to run boto integration tests too

What is ddbmock not useful for ?

Do not use it in production or as a cheap DynamoDB replacement. I’ll never stress it enough.

All the focus was on simplicity/hackability and simulation quality. Nothing else.

What is ddbmock useful for ?

  • FAST and RELIABLE unit testing

  • FAST and RELIABLE functional testing

  • experiment with DynamoDB API.

  • RELIABLE throughput planification

  • RELIABLE disk space planification

  • almost any DynamoDB simulation !

ddbmock can also persist your data in SQLITE. This open another vast range of possibilities :)

Current status

  • pass all boto integration tests

  • support full table life-cycle

  • support full item life-cycle

  • support for all item limitations

  • accurate size, throughput reporting

  • no limits on concurent table operations

  • no limits for request/response size nor item count in these

See for detailed up-to-date status.


  • v1.0.0 (*): full documentation and bugfixes

  • v0.4.1: schema persistence + thread safety, bugfixes

  • v0.4.0: sqlite backend + throughput statistics + refactoring, more documentation, more tests

  • v0.3.2: batchWriteItem support + pass boto integration tests

  • v0.3.1: accuracy in item/table sizes + full test coverage

  • v0.3.0: first public release. Full table lifecycle + most items operations

(?) indicates a future release. These are only ideas or “nice to have”.

Example usage

Run as Regular client-server

Ideal for test environment. For stage and production I highly recommend using DynamoDB servers. ddbmock comes with no warranty and will loose your data(tm).

Launch the server

$ pserve development.ini # launch the server on

Start the client

import boto
from ddbmock import connect_boto_network

# Use the provided helper to connect your *own* endpoint
db = connect_boto_network()

# Done ! just use it wherever in your project as usual.
db.list_tables() # get list of tables (empty at this stage)

Note: if you do not want to import ddbmock only for the helper, here is a reference implementation:

def connect_boto_network(host='localhost', port=6543):
    import boto
    from boto.regioninfo import RegionInfo
    endpoint = '{}:{}'.format(host, port)
    region = RegionInfo(name='ddbmock', endpoint=endpoint)
    return boto.connect_dynamodb(region=region, port=port, is_secure=False)

Run as a standalone library

Ideal for unit testing or small scale automated functional tests. Nice to play around with boto DynamoDB API too :)

import boto
from ddbmock import connect_boto_patch

# Wire-up boto and ddbmock together
db = connect_boto_patch()

# Done ! just use it wherever in your project as usual.
db.list_tables() # get list of tables (empty at this stage)

Note, to clean patches made in boto.dynamodb.layer1, you can call clean_boto_patch() from the same module.


  • Python 2.7.x

  • Pyramid >= 1.3

  • Boto >= 2.5.0 (optional)

  • NO AWS account :)

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