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203 Stars 139 Forks Apache License 2.0 239 Commits 52 Opened issues


Low-level, Protobuf-based Java and Python client libraries for Cloud Datastore. Check out google-cloud-java and google-cloud-python first!

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Google Cloud Datastore

Note: This repository contains low-level Java and Python client libraries for Google Cloud Datastore. For more idiomatic and usable client libraries in these languages, please visit the Google Cloud Client Libraries for Java and Google Cloud Client Libraries for Python repositories. You can also find the full list of supported client libraries in a variety of languages on the Client Libraries page of Cloud Datastore.

Cloud Datastore is a highly-scalable NoSQL database for your applications. Cloud Datastore automatically handles sharding and replication, providing you with a highly available and durable database that scales automatically to handle your applications' load. Cloud Datastore provides a myriad of capabilities such as ACID transactions, SQL-like queries, indexes and much more. For more information, see the Cloud Datastore documentation.

This repository contains clients that are deliberately low-level and map directly to the underlying Datastore RPC model. They're designed to provide more flexibility to developers and higher level library implementers.



Client Libraries

You can learn more about client libraries for Cloud Datastore here.

pip install googledatastore
  • Java (Maven):


For more information, see the Cloud Datastore documentation.

Filing Issues

  1. For production issues and support options, see Cloud Datastore support.
  2. For bugs or feature requests, please first look at existing issues.
  3. When applicable, create a new report. Note that this repo exclusively covers the low-level, Protobuf-based clients. If you're using
    (Java) or
    (Python), please file your issue in the appropriate repo, google-cloud-java or google-cloud-python. If you file an issue with either of those client libraries here, we will (gently) redirect you to the right repo and close the issue in this one.
  4. For bugs, detail the steps to reproduce the problem and the affected version number.
  5. For feature requests, articulate the use case you are trying solve and describe any current workaround(s).

Contributing changes


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