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.
Your upcoming app can be built faster on a fully managed SQL database and can be moved into Azure with a few to no application code changes. Flexible and responsive server less computing and Hyperscale storage can cope with your changing requirements and one of the main benefits is the reduction in costs, which is noticeable.
Maintenance is always an issue, so using a cloud solution saves a lot of trouble.
On premise solutions always suffer from fragmented implementations here and there, where several "dba's" keep track of security and maintenance. With a cloud database it's much easier to keep a central overview.
Security options in SQL database are next level... data masking, hiding sensitive data where always neglected on premise, whereas you'll get this automatically in the cloud.
One needs to be aware that some T-SQL features are simply not available.
The programmatic access to server, trace flags, hardware from within Azure SQL Database is taken away (for a good reason).
No SQL Agent so your jobs need to be orchestrated differently.
The maximum concurrent logins maybe an unexpected problem.
Sudden disconnects.
The developers and admin must study the capacity and tier usage limits https://docs.microsoft.com/en-us/azure/azure-subscription-service-limits otherwise some errors or even transaction aborts never seen before can occur.
Only one Latin Collation choice.
There is no way to debug T-SQL ( a big drawback in my point of view).
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
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.
We moved away from Oracle and NoSQL because we had been so reliant on them for the last 25 years, the pricing was too much and we were looking for a way to cut the cord. Snowflake is just too up in the air, feels like it is soon to be just another line item to add to your Azure subscription. Azure was just priced right, easy to migrate to and plenty of resources to hire to support/maintain it. Very easy to learn, too.
