Google Cloud Spanner vs. Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

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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If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.

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• Super high availability
• Scales automatically
• High standard SLA

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• Apache MADlib provides popular machine learning functionality.
• Allows you to query terabytes of data databases.
• Interoperability for AWS S3 is effortless.

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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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• Running on Azure is a little more difficult.
• Synchronization with Kafka may be a little easier.

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They were very helpful. We needed support for initial implementation.

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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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• 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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• There was a noticeable reduction in system reliability.
• Saw a reduction in unsuccessful analytics operations.

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Independently Invited by TrustRadius

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