Amazon DocumentDB (with MongoDB compatibility) vs. Google Cloud Datastore

AWS Document DB (with MongoDB compatibility) is well suited when for all the workloads due to its huge feature offerings which will reduce our operational overhead and due to that we can focus more on our WorkLoad rather than optimising and fine tuning Databases. Its Offerings are Advanced Monitoring, DB cluster Upgrades, Migration Assistant, High Availability, Fault Tolerance, Data Durability, Security, Storage Auto Scaling, Backup Restore policies.AWS Document DB (with MongoDB compatibility) some of the features that are there in some other services like MongoDB Atlas that offers vast amount of features plus Supports Multi Cloud while Deploying Database clusters, Immediate support to latest Mongo DB versions, Mobile & Edge Sync like Atlas Edge Sync, Freedom to choose Database deployment in Any top Public Cloud, Having more then 100 plus Monitoring and Telemetry metrics for index and schema recommendations, More Compatibility with MongoDB queries.

Incentivized

Using Google Cloud Datastore in conjunction with Google AppEngine was a very seamless integration and much easier than using other datastores since so much of the configuration is abstracted for you. Because of this, creating simple applications is very easy and getting Google Cloud Datastore to power the backend ties everything together. If we were using Google Compute Engine, I'd imagine the same seamless experience would be there as well.

Incentivized

• Amazon DocumentDB (with MongoDB compatibility) provides Auto scaling of cluster as a by default functionality through this we can focus on more on our applications end
• Through AWS Document DB without much operation overhead we can configure for Database's high availability, Durability, Backup Restores policies, Advanced Monitoring, Security Parameters.
• Also they can provide us a Guide for Database Migration from any Supported Mongo DB vendor to AWS Document DB.
• Via AWS Document DB query Logging ( Profiling ) we can fine tune our database queries and hence improving our END to END Customer Experience and Product Enhancements.

Incentivized

• It is hosted in GCP, our primary cloud provider.
• It integrates with all the services we use in GCP.

Incentivized

• Give support for Latest Mongo DB versions available in market
• AWS Document DB is limited up to 32 shards per cluster and 2 shards per Document DB instance and all within single region
• Start supporting more numbers of Rich data types
• Should have access to MongoDB experts who throw light on Cutting edge mongoDB features and integration consulting.

Incentivized

• Part of the Google Cloud Platform walled garden.
• Pay for read/writes to the datastore, in addition to storage.
• Not many libraries exist.

Incentivized

I give Google Cloud a full score because it satisfies our needs so well. We host most of our infrastructure on Google Cloud and using Google Cloud Datastore helps us to solve our NoSQL storage problem. and Google Cloud Datastore is so scalable and elastic. It saves us lots of time to maintain and saves us money.

Incentivized

We selected Google Cloud Datastore as one of our candidates for our NoSQL data is because it is provided by Google Cloud, which fits our needs. Most of our infrastructure is on Google Cloud, so when we think about the NoSQL database, the first thing we thought about is Google Cloud Datastore. And it proves itself.

Incentivized

• Great Customer Experience as DB queries are fine tuned
• Less Operational Overhead to manage and take care of the Database
• Automatic applying of Small patches

Incentivized

• Simple billing part of Google Cloud Platform
• No time spent configuring and maintaining Google Cloud Datastore.
• Very good uptime for our applications.

Incentivized