Google Cloud Spanner vs. Google Cloud 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.

Incentivized

Although Google Cloud SQL has room for improvement by addressing a minor lack of features, its features and services keep it high among other SQL database products. It is very fast compared to others. Since it is cloud-based, maintenance is also easier. Integration capabilities are also more than expected.

Incentivized

• Super high availability
• Scales automatically
• High standard SLA

Incentivized

• Highly scalable without worrying about sudden transaction explosion during peak hours.
• Highly available with multiple geographical locations and regions for nearly 0 downtime to the users.
• Extremely reliable and responsive for high latency applications due to superb networking at the core.

Incentivized

• 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.

Incentivized

• Increasing support for more database engines may enable a wider range of application needs to be met.
• Implementing and updating cutting-edge security features on a constant basis.
• Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.

It's a great product with ease of use, great scalability and high availability. There's no need to have high effort on administration. Great visibility to what happens on database like CPU, memory, IO. We can also see the performance based on query. Overall good experience and really recommend it to others.

Incentivized

GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.

Incentivized

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.

Incentivized

Google SQL was great as a first SQL provision. It quickly enabled the apps to be built and scaled as needed for a while. It was robust and adaptable as needed and easy to export as needed when ready, depending on growth. Cost-wise, it's a good choice and requires little investment to get going.

Incentivized

• 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

Incentivized

• With managed database system, it has given us near 100% data availability
• It has also improved web layer experience with faster processing and authentication using database fields
• Google Cloud SQL also gels up well with Google Analytics and other analytics systems for us to join up different data points and process them for deeper dives and analysis

Incentivized