Likelihood to Recommend It’s great for server less and real-time applications. It would be great for gaming and mobile apps. However, if you need relational database and have fixed budget, do not use it. While budget can be managed, you need to be careful. Also this is not a tool for storing big data, there are other wide-column database types you could use for it ins the ad
Read full review 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.
Read full review Pros To manage varying workloads, it enables users to increase capacity as necessary and decrease it as needed. Users can take advantage of its auto-scaling, in-memory caching, and backup without paying for the services of a database administrator. We can use it for low scale operations. Read full review 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. Read full review Cons Cost model may not be easy to control and may lead to higher costs if not carefully planned Indexing may be a cost culprit when not planned, because it's not included on the data costs The Query Language may not fulfill everybody's expectations, as it has less features than those of competitors. Read full review 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. Read full review Likelihood to Renew It's core to our business, we couldn't survive without it. We use it to drive everything from FTP logins to processing stories and delivering them to clients. It's reliable and easy to query from all of our pipeline services. Integration with things like
AWS Lambda makes it easy to trigger events and run code whenever something changes in the database.
Read full review Usability Functionally, DynamoDB has the features needed to use it. The interface is not as easy to use, which impacts its usability. Being familiar with AWS in general is helpful in understanding the interface, however it would be better if the interface more closely aligned with traditional tools for managing datastores.
Read full review 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.
Read full review Performance It works very well across all the regions and response time is also very quick due to AWS's internal data transfer. Plus if your product requires HIPPA or some other regulations needs to be followed, you can easily replicate the DB into multiple regions and they manage all by it's own.
Read full review Support Rating I have not had to contact support for this service, however I have had to contact AWS for other services and their support has been good.
Read full review 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.
Read full review Alternatives Considered The only thing that can be compared to DynamoDB from the selected services can be Aurora. It is just that we use Aurora for High-Performance requirements as it can be 6 times faster than normal RDS DB. Both of them have served as well in the required scenario and we are very happy with most of the AWS services.
Read full review 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.
Read full review Scalability I have taken one point away due to its size limits. In case the application requires queries, it becomes really complicated to read and write data. When it comes to extremely large data sets such as the case in my company, a third-party logistics company, where huge amount of data is generated on a daily basis, even though the scalability is good, it becomes difficult to manage all the data due to limits.
Read full review Return on Investment Some developers see DynamoDB and try to fit problems to it, instead of picking the best solution for a given problem. This is true of any newer tool that people are trying to adopt. It has allowed us to add more scalability to some of our systems. As with any new technology there was a ramp up/rework phase as we learned best practices. Read full review 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 Read full review ScreenShots Amazon DynamoDB Screenshots Google Cloud SQL Screenshots