Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
Cloud BigTable
Score 8.6 out of 10
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Google's Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability.
DynamoDB is a great service if you are looking for a quick and easy way to store NoSQL data in the cloud and do not want to be concerned with managing the server or infrastructure. If you are already invested in AWS, the value proposition is even higher as it works very well with the other services that AWS provides.
Google Bigtable is ONLY suited for massive data sets which scale PetaBytes and TerraBytes. Anything under this can easily be done via dedicated VMs and open source tools. Google Bigtable is expensive and shall be used wisely. It should be utilised only where it is well suited else you would simply be wasting dollars and not utilizing its full benefits.
Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.
User interface's responsiveness: I understand so much is going on under the hood, but laggyness is acceptable if a workload is running or being processed. In case their is not workload being process, GUI should work blazing fast. I have faced this at times, and this becomes frustrating as well.
Nothing other than this - BigTable is quite efficient platform and does exactly what it is built for.
We will most likely continue to use DynamoDB for certain use-cases. If we stopped using DynamoDB as often, it would likely be because we started using Aurora Serverless more. Aurora Serverless may offer similar availability, management and cost benefits while allowing developers to use their MySQL tools and experience.
It has a big learning curve to understand the keys and the efficient ways to store data, and I don't think the AWS documentation does a good job of explaining it, and rather markets DynamoDB to people who have prior knowledge of why noSQL databases work the way they do. I found MongoDB easier to use, but DynamoDB easier to set up.
For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.
We evaluated using MongoDB or Amazon DyanmoDB. For us, the biggest advantage is that there's no maintenance cost for Amazon DynamoDB. Mongo gets complicated when you setup sharding. With Amazon DynamoDB, it's literally a push of button to increase throughput. This saves time and money on DevOps resources.
Since the Amazon manages the instance, the amount of time a developer needs to spend configuring the database is less. For comparison, if we were to manage the same instance manually, we need to set up EC2 instance, install the DB, setup backup scripts, track backup failures, which is a great overhead for the dev. Using DynamoDB this overhead is reduced and hence having a great ROI.
Great documentation and easy setup makes an easy learning curve to transition to DynamoDB. Only caveat is as with any database, the data structure should be thoroughly analyzed for types of querying because there are limitations with the DynamoDB API.
Ties very well with rest of the Amazon eco system. Having rest of the applications in Amazon allows managing the application security a breeze.
