Amazon DynamoDB

In my experience, we've found that DynamoDB has made it very easy for us to denormalize data and transition those pieces of data/functionality to AWS. The NoSQL structure makes it much simpler for us to implement data sharing use cases versus our existing implementation of SQL. Outside of these cases, we haven't found a big enough advantage over our current SQL structure to warrant switching over.

Here are the few reasons to highly choose DynamoDB:
1. It is managed, no need to invest in time or resources to do the upgrades or worry if it is up or not.
2. It has predictable performance.
3. Sits well with the other components of AWS.
4. It has multiple interfaces to connect and work on.
5. Automatic partition support.
6. Gives great scalability especially during peak performance needs.

Amazon DynamoDB is a NoSQL database so use it to collect big data that comes in at a high velocity and don't expect it to handle a transactional workload.

Amazon DynamoDB is very well suited when you are already running other Amazon services and/or already have the data in AWS. It is also well suited when the queries are simple and there is no need to file tune the underlying infrastructure. It is not well suited when the amount of data is very large and there is some expectation of the capacity needed upfront without any major peak workload considerations.

If you are in a company that seeks to implement NoSQL service to save the hassles of a relational database, DynamoDB is the service to use. Especially if you use Amazon Web Service already. It can be a huge help to your company's data structure. It saves you a lot of money as you pay as you go.

Good for times where a non-relational database is needed and speed is an absolute must. If the data is relational like SQL, then DynamoDB does not work as well for the purposes that the service serves.

Amazon DynamoDB is great for mid to enterprise-level organizations. The ease of setup, performance, and reliability are key factors to our organization. For organizations that are smaller than mid to enterprise-level, the cost of running DynamoDB compared to on-prem could get very expensive.

A simple key-value store, with properly distributed keys, works pretty well with DynamoDB. However, where it really shines is when effective range keys are used. Anything with semantic ordering works really well, but even multiple documents of scoped data work pretty well. As with all things DynamoDB, you have to be very intentional with your partition key.

Amazon DynamoDB is very well suited for applications where the data is in semi-structured, unstructured, or basically in a key/value model. It is also an apt choice if you have a need for high performance, low latency, auto-scaling and cost-effective solution where you don't need to buy any inventory or server or memory space in advance for the whole lifecycle of the project. It doesn't require any installation and is serverless as well. It basically comes into the ecosystem of Amazon Web Services. So, if your data is located on Amazon or you are already making use of AWS then this can be a perfect fit for your project
It also encrypts the data with the latest security algorithm available and our customers are also quite relaxed knowing that their data is stored on Amazon cloud and it secured by Amazon.

If your database doesn't have any relations DynamoDB would be an ideal solution. Consider it more as key-value storage rather than a database, so it ideal for storing something based on a key and fetching it back using that key. But if you have relations or complex data-based queries DynamoDB might not have a straight forward solution.

It is ideal for those projects where you need to store a large amount of data, but you do not know how many will be so you need the database to increase its storage capacity together with the number of users, without having to spend extra money, it also has a great potential thanks to the fast connection it offers, so the data travels at high speed, and this speeds up the performance of the applications, excellent for projects where non-relational databases are used and what matters is to store large quantities of information and use them at high speed.

The best scenario is when one needs to deal with very large volumes of data in inconsistent formats.

The worst case, I would think, is the use cases when the data is strictly structured and interrelated. Also when the volumes are not so great or the project is small and there can be budgetary concerns.

Cloud-native serverless applications get accelerated when using Dynamo DB.

We've used DynamoDB to store online form submissions where forms can have differing information, identify changes between data sets, storage for vast amounts of large data-sets for analytics. Each of these scenarios has pros/cons versus using other traditional methods. It is more about accomplishing what you need to. DynamoDB allows for an increase in Read/Write IOs and allows scalability that some other traditional methods do not. Though it doesn't include some of the nice structure that traditional methods.

We are using Dynamo for session management in a web application, storing the product catalog, storing questions(different question types in a survey, subjective-objective, single select multiple select), storing survey responses, storing email templates, and storing application logs.

It's a very good database for specific use-cases, but you should know full well what you are getting into with it. You are stuck doing things the Amazon way and paying much more than other options. If you need speed, have the money, and fully understand your indexes, it's top notch. If you care more about tooling, known costs, and stability, another solution might be better.

You should not worry about scaling with this tool. For beginners, it's not easy to understand how partition key and sort key work.

Fast, reliable access to a large amount of data has been key for us. However, if you're looking for a traditional relational database, this is certainly not the place to look. I'd also recommend this solution regardless of whether or not you're existing infrastructure is already in AWS or not - I'd say it's a good fit for any setup.

Great for temporary data storage or data that has a particularly short lifecycle and can be processed then disposed of quickly. I would not recommend DynamoDB for any long-standing applications or user-based systems. DynamoDB data should be ingested, processed, analyzed, then removed. The infrastructure setup allows for confidence that your data will be there when you need it but only for a short period of time. Backups are not worth the effort, so keep that in mind.

Amazon DynamoDB is absolutely the easiest and most efficient way to run a Non-Relational database. It's perfectly suited for a "source of truth" where other indexes might be built from data stored in DynamoDB, and for use where search patterns are predictable. It's also incredibly effective at storing relatively unstructured data, or data models that might frequently change. As it does not require a rigid definition of data beforehand, it makes adjusting data stored in the table a non-effort, but it does require some planning when looking at how to get data back out of the table.
Unlike traditional SQL or Relational databases, DynamoDB is designed to have all relevant information within a single object. If not properly planned, this can lead to issues when building out a front-end. DynamoDB does not have join table support, nor does it support complex searches or "count" style responses. It is eventually consistent, although they recently did introduce Transaction support, there is no "rollback" option.

DynamoDB is great for any situation where you need to store some piece of data temporarily. User sessions in a web app is a great example. You can also store information more permanently if you don't need to do complex queries on the data or always know the ID of what you're looking for. In our situations, we've made the mistake of putting data into DynamoDB and realized later that we needed to query the data with a more complex, relational type of query and discovered we could not efficiently do so. So, if your queries are simple, DynamoDB can be a really simple straightforward solution.

DynamoDB is great for two cases. The first is for services that do not experience high loads or demand high availability. DynamoDB is inexpensive, and it provides great developer velocity. The second is for applications that demand high performance, have well-understood requirements, and a narrow range of queries.

It's no replacement for a SQL database, but if you want a NoSQL data storage solution with some rigidity, it's the one to go for.