10 DynamoDB Advantages & Disadvantages [2026]

## 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.