Google Cloud Datastore vs. Google Cloud Spanner

I feel like Google Cloud Datastore is well suited when the data models are simple and the possible filtering and sorting operation are not complex. With more complex filtering, the amount of required indexes increase, and so does the costs.

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Google Cloud Spanner is suited for limitless horizontal scaling while maintaining strong consistency which needs to support ACID. NoSQL databases work in scaling but no ACID support. RDBMS support ACID, but horizontal scaling is not as great. The API it provides result in some limitations to related areas of the code, such as connection pools or database linking framework. So high # of connection pools can vary.

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• It is hosted in GCP, our primary cloud provider.
• It integrates with all the services we use in GCP.

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• Super high availability
• Scales automatically
• High standard SLA

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• Part of the Google Cloud Platform walled garden.
• Pay for read/writes to the datastore, in addition to storage.
• Not many libraries exist.

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• Support for Views
• Support for more databases (schemas).
• More index types that can be supported (Functional)
• Backups (ie table/data backup) if data is deleted or truncate by accident.

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I give Google Cloud a full score because it satisfies our needs so well. We host most of our infrastructure on Google Cloud and using Google Cloud Datastore helps us to solve our NoSQL storage problem. and Google Cloud Datastore is so scalable and elastic. It saves us lots of time to maintain and saves us money.

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The simple implementation, together with the Google Cloud dashboard that allows data inspection, editing and querying, makes Google Cloud Datastore a comprehensive choice when it comes to NoSQL databases.

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If deploying an application in Google Cloud Platform, using Google Cloud Datastore is a no brainer because of the simplicity of setup. Other options would require more setup and configuration, and do not come with the same level of guaranteed uptime as Google Cloud Datastore. In our case, we've been using Google Cloud Datastore for 4 years without any issues and have never had to think about it.

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At that point, we were looking at something [that] can hold our relational database, [...] provide stable connection, and maintain high ACID transition. BigTable is for nonrelational database so it was out of our [sight] very quickly. BigQuery is a data warehouse that can hold huge amount of data but not ideal for transition. AWS RDS is [...] similar to Spanner but because most of our services are already on GCP, so we went with Spanner.

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• It solves our NoSQL database problem.
• It it highly scalable and available to meets our needs.

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• Backups specifically if transactional data is deleted. Restoring made us lose time.
• Sharding on Horizontal level was quick and easy. Deployment and increasing nodes is easy
• Large dataset handling.
• ACID compliance

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info