204 Reviews and Ratings
13 Reviews and Ratings
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
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
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.Incentivized
Super high availabilityScales automaticallyHigh standard SLAIncentivized
Cost model may not be easy to control and may lead to higher costs if not carefully plannedIndexing may be a cost culprit when not planned, because it's not included on the data costsThe Query Language may not fulfill everybody's expectations, as it has less features than those of competitors.Incentivized
Support for ViewsSupport 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
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.Incentivized
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.Incentivized
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.Incentivized
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.Incentivized
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.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
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.Incentivized
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.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 easyLarge dataset handling.ACID complianceIncentivized