10 DynamoDB Advantages & Disadvantages

DynamoDB is one of the most popular and widely used NoSQL databases in today's market. It is a fully managed database offering that allows developers to focus on application development without worrying about managing the underlying infrastructure.

It also offers single-digit millisecond response times, high availability, globally accessible tables, and enhances the usability and the user experience. Large, well-renowned clients with millions of users currently leverage the features of DynamoDB for their applications to provide a flawless user experience.

Although it provides those standout features, we need to be aware of the advantages and disadvantages of DynamoDB before using it in our projects. So, let's discuss the pros and cons of DynamoDB to get a better understanding.

Advantages Of Using DynamoDB

1. Scalability

DynamoDB provides virtually unlimited storage, and users can utilize it as required. In addition, it provides flexibility for the developers to only scale the database once the application starts accumulating data and not at the start. So, there is no need to have reserve storage when deploying the database. DynamoDB also supports both vertical and horizontal scaling, making it suitable for applications with varying workloads. The auto-scaling feature dynamically adjusts throughput capacity based on traffic patterns, ensuring optimal performance without manual intervention.

2. Seamless Data Replication

By default, DynamoDB replicates table data in 3 availability zones within a single region. It allows you to easily recover from any disaster and avoid service disruptions.

In addition, you can use DynamoDB global tables to replicate data across multiple regions (different geolocations) to achieve a higher level of redundancy. This feature is particularly useful for applications that require high availability and low-latency access to data from different parts of the world.

The data replication takes place in near real-time to ensure seamless failover during a disaster while minimizing the data lost. This global replication also supports multi-active writes, allowing applications to write data to multiple regions simultaneously, which is beneficial for globally distributed applications.

3. Fully Managed (Serverless)

DynamoDB is a fully managed NoSQL database service that does not require users to maintain any underlying infrastructures. Instead, it allows users to focus on developing their applications. At the same time, AWS handles tedious tasks such as high availability, database upgrades, and even maintaining the physical infrastructure within their data centers. This serverless nature also means that you only pay for the resources you consume, which can lead to cost savings. Additionally, DynamoDB integrates seamlessly with other AWS services, such as Lambda and API Gateway, to build scalable and event-driven architectures.

4. Secure

The DynamoDB database service provides clear, demonstrated security guidelines while adhering to multiple globally recognized regulatory compliance like PCI DSS, HIPAA, and NIST.

It is important to note that even though AWS secures the infrastructure of the database service, DynamoDB depends on the shared responsibility model and expects its users to securely configure their DynamoDB instances using the required security controls.

DynamoDB also supports integration with AWS Identity and Access Management (IAM) to enforce fine-grained access control to the database while using industry-accepted algorithms to encrypt the data. Additionally, DynamoDB supports encryption at rest and in transit, ensuring that your data is protected at all times. The service also offers VPC endpoints to ensure secure and private connectivity between your VPC and DynamoDB.

5. Fast Response Times

One of the most talked about advantages of DynamoDB is the single-digit millisecond response times. These response times are significant since DynamoDB ensures lightning-fast response times at any scale.

However, if these response times are not fast enough, you can use DynamoDB Accelerator (DAX) caching mechanism to decrease the latency of the DynamoDB operations. DAX can provide microsecond response times for cached read-heavy workloads, further enhancing the performance of your application. This makes DynamoDB suitable for use cases requiring real-time data access, such as gaming leaderboards, IoT applications, and financial trading platforms.

Disadvantages Of Using DynamoDB

1. Limited Querying Options

Even though DynamoDB can store large amounts of data, querying data from within a DynamoDB database is tedious due to the limited querying options that the service provides.

The service relies on the indexes for querying tasks and does not allow querying if no indexes are available. An alternative is to scan the entire table to query the data. However, this operation requires a significant amount of read capacity units, which becomes an expensive task once the database scales up. Additionally, complex queries involving multiple attributes can be challenging to implement. Developers often need to carefully design their data models and indexes upfront to ensure efficient querying.

2. Difficult To Predict Costs

DynamoDB allows users to select a suitable capacity allocation method depending on the use case.

The users may opt for the provisioned capacity model if the application has a predictable amount of traffic and requests. In this model, DynamoDB allocates a specified amount of read and write units, and it will keep the resources available even if there is no significant utilization.

The on-demand capacity allocation model automatically adjusts the read and write capacity based on the number of requests sent to the database service. This model suits well for applications that have unpredictable spikes of requests.

Even though the flexibility of the on-demand model allows for seamless scaling, one of the significant drawbacks of using this model is its unpredictable and expensive costs. Monitoring and managing costs can become complex, especially for applications with highly variable workloads. AWS provides cost management tools, but they require careful configuration and monitoring to avoid unexpected expenses.

3. Unable to Use Table Joins

DynamoDB has limited options for querying the data within its tables and restricts the complexity of the queries.

The database service makes it impossible to query information from multiple tables as it does not support table joins. It becomes a significant drawback since the developers cannot perform complex queries on the data, which are possible in some other competitive products. This limitation often requires developers to denormalize their data, which can lead to data redundancy and increased storage costs. To mitigate this, developers need to carefully design their data models to minimize the need for joins.

4. Limited Storage Capacities For Items

DynamoDB sets restrictions on most components, which is no different from the limits set for each item size within a DynamoDB table.

The size limit for an item is 400KB, and it is essential to note that the users cannot increase this value in any way. This limitation can be restrictive for applications that need to store large objects or documents within a single item. Developers may need to use additional storage solutions, such as Amazon S3, for storing large objects and reference them within DynamoDB items.

5. On-Premise Deployments

DynamoDB is one of the most successful cloud-native, fully managed database services available in today's market. The service is available for all AWS users keen to deploy their databases on the AWS cloud.

Even though the solution has many benefits, one of the major drawbacks is that the solution lacks an on-premise deployment model and is only available on the AWS cloud. This limitation does not allow users to use DynamoDB for applications that require an on-premise database.

Although DynamoDB does not offer an on-premise deployment for production environments, it offers an on-premise deployment for development or testing. But, this deployment does not have the same high speeds we expect from DynamoDB and is strictly only for testing. For organizations with strict data residency requirements, this can be a significant limitation.

6. Learning Curve and Vendor Lock-In

Using DynamoDB effectively requires a good understanding of its unique data modeling principles, which can be different from traditional relational databases. This learning curve can be steep for developers who are new to NoSQL databases. Additionally, since DynamoDB is a proprietary service offered by AWS, there is a risk of vendor lock-in. Migrating to another database service in the future could be complex and costly. Organizations need to weigh the benefits of DynamoDB against the potential challenges of vendor lock-in and consider long-term strategies for data portability.

Conclusion

In this article, I have discussed some of the key benefits that make DynamoDB an appealing solution and some drawbacks that limit certain aspects of deployments. I hope this article will help you to decide the suitability of DynamoDB for your application. Thank you for reading!