DynamoDB and Redis are the two most preferred data storage solutions used in software applications because of their unique strengths and capabilities. While DynamoDB is used in high-performing and low-latent applications, Redis is used as an in-memory data store that supports real-time data operations.
As a best practice, it’s beneficial to compare the features and limitations of these databases before using them.
Let us look into the details of DynamoDB vs Redis to understand different scenarios in which each of these databases can excel. It will help you make an informed decision on what suits your application and budgetary constraints better.
What is DynamoDB?
Amazon DynamoDB is a fully managed NoSQL database solution offered by Amazon Web Services (AWS). It is used to develop high-throughput applications with single-digit millisecond performance scale.
DynamoDB's high efficiency is mainly due to its support for the global tables feature. Global tables are multi-region database tables supporting multi-active data replication. They enable you to replicate your data across multiple regions, ensuring better data availability.
To utilize DynamoDB effectively, you can integrate it with other AWS services such as AWS S3, AWS CloudFormation, AWS CloudWatch, and AWS Auto Scaling. This adds to its ease of use for building applications for financial services, gaming, or streaming services.
Key Features of DynamoDB
- Serverless: DynamoDB's serverless architecture eliminates the need to manually manage installations, servers, and other maintenance operations. It provides zero downtime maintenance and minimal disruptions during upgrades and migrations.
- NoSQL: You can work with non-relational data, including documents and key-value pairs, in DynamoDB because of its NoSQL data model. It also offers better flexibility and scalability than most traditional RDBMS.
- Change Data Capture (CDC): DynamoDB allows you to capture item-level modifications made in your DynamoDB tables using DynamoDB Streams and Kinesis Data Streams. Your application can access this modified data in near real-time.
What is Redis?
Redis is an in-memory data storage system that stores data as key-value pairs. It supports different data types, including strings, lists, hashes, and sets. Redis allows you to perform atomic operations on these data types. This includes appending to a string, adding an element to a list, incrementing a value in a hash, or computing a set intersection or union.
You can perform asynchronous data replication in the Redis database. This process involves a latency between writing the data on the master instance and the replica receiving it. In addition, the database also supports synchronous data replication using the WAIT command; it works by blocking the client until the specified number of replicas acknowledge receipt of the command. However, this doesn’t fully eliminate the risk of data loss in case of any major failure that may affect all synchronized nodes simultaneously.
To utilize all these features of Redis, you can deploy it easily on several POSIX systems, including Linux, Mac OS X, and *BSD.
Key Features of Redis
- Scalability: You can scale Redis horizontally using sharding by adding extra nodes to clusters. This allows you to split your high-volume dataset across multiple nodes.
- Pub/Sub Messaging: Redis supports pub/sub messaging, an asynchronous communication model in which the publisher and subscribers do not directly interact with each other. They are decoupled to facilitate flexibility and scalability.
- Time-to-Live (TTL): This feature helps you to set a time limit after which data records in your Redis database are automatically removed. It ensures efficient use of memory for caching and session management.
Key Differences Between DynamoDB vs Redis
Here are some key differences between Amazon DynamoDB vs Redis:
Data Structure
DynamoDB is a NoSQL database that allows you to store data as key-value pairs and as JSON-like documents. Redis, on the other hand, is an in-memory data storage system that enables you to store data as key-value pairs.
Architecture
Tables and secondary indexes are two major components of DynamoDB’s architecture. A table consists of rows and columns known as items and attributes, respectively. To retrieve data from items, you must use primary keys. Sort keys are used with primary keys to filter data more precisely during queries. DynamoDB also uses secondary indexes, which are data structures that contain a subset of attributes to further speed up the data retrieval process. They are classified into two types: global secondary indexes and local secondary indexes.
Conversely, Redis offers three main architecture setups: Standalone, Sentinel, and Cluster. The Standalone consists of only one node and is easier to deploy but does not ensure data reliability. Redis Sentinel has a distributed structure with master and replica instances. The Cluster architecture consists of multiple nodes to enable you to distribute data across it for continuous operations.
Data Durability
Along with the use of global tables, DynamoDB ensures high data durability by replicating data across three Availability Zones within an AWS region. It also facilitates continuous data backups, point-in-time recovery, and on-demand backup and restoration of your data.
In contrast to this, Redis helps with data persistence by allowing you to take periodic snapshots of your database or by logging all the write operations on disk.
Costs
DynamoDB charges based on whether you are using its on-demand capacity mode or provisioned capacity mode. Each has different costs for reading, writing, and storage services.
Redis offers self-managed and cloud-based deployment options. In the self-managed option, you can manage the database on your local system or virtual cloud machine, but it often involves higher maintenance costs. The cloud version has three options: Essentials (free), Essentials (paid), and Cloud Pro.
You can compare DynamoDB vs Redis costs to decide which database to use depending on your budget and task objectives.
Factors to Consider When Choosing DynamoDB or Redis
Some of the factors that you should consider while choosing DynamoDB or Redis are as follows:
Performance
DynamoDB provides a performance with a latency in the single-digit millisecond range. However, it allows you to store data on disk, increasing its latency compared to Redis.
On the other hand, Redis is an in-memory data storage system with a latency range of sub-microseconds. It is an excellent solution for low latency and real-time applications.
This comparison of DynamoDB vs Redis latency range indicates that you can choose DynamoDB if a slight delay in operations or outcomes is acceptable in your application. However, if you want to perform all the operations quickly or in real-time, you can opt for Redis.
Scalability
DynamoDB supports autoscaling that enables it to adjust its resources automatically for increasing data volumes. It also offers the global table feature, facilitating data replication across various regions and nodes, ensuring data availability and scalability.
In contrast to DynamoDB, Redis allows horizontal scaling through sharding, which requires manual configuration.
To save time and effort, you can use DynamoDB to leverage its auto-scaling capabilities.
Use Cases
DynamoDB is suitable for use in low-latency and high-performing web or mobile applications for gaming and streaming. It is also used for real-time analytics in social media platforms, the stock market, and e-commerce portals.
Redis is used as a message broker for data transfer between different systems. You can use it for caching in high-performing applications that require faster data retrieval. Moreover, Redis is useful for session management to handle high website or application traffic. Owing to these capabilities, the StackOverflow survey shows that 7007 developers who used Redis in 2024 want to continue using it, making Redis a popular database service.
Integrating Data into DynamoDB or Redis Using Airbyte
Integrating data in DynamoDB or Redis is essential to leverage the capabilities of the platform for real-life applications. You can use Airbyte, an ELT data movement platform, for effective data integration. It offers an extensive library of 400+ connectors to load data from source to target data systems.
Airbyte supports DynamoDB and Redis as destination connectors, allowing you to integrate data from any source into these databases. It also offers DynamoDB as a source connector, which you can use to load data from DynamoDB to Redis.
If the connector of your choice is not available in the existing set of connectors, you can build your own using Airbyte’s Connector Development Kit (CDK). You can then clean and transform the integrated data with suitable tools to use for analytics, security, or data backups in different applications.
Some of the important features of Airbyte are as follows:
- Multiple Data Sync Modes: You can synchronize your target data system with the source using different sync modes supported by Airbyte. It includes incremental append, incremental append + deduped, full refresh append, full refresh overwrite, and full refresh overwrite + deduped modes.
- Orchestrate Your Data Pipelines: Airbyte supports integration with data orchestration tools like Apache Airflow or Dagster to streamline data pipelines.
- Custom Transformations Using dbt: You can utilize the Airbyte-dbt Cloud integration to clean and transform raw data into a format suitable for data analysis and reporting.
- Automated Chunking and Indexing: Airbyte’s automatic chunking and indexing feature helps you transform raw data and store it into different vector databases supported by the platform. It also enables you to generate embeddings using pre-built LLM providers supporting compatibility across OpenAI, Cohere, and other popular LLMs.
Conclusion
DynamoDB and Redis are two highly functional databases that can be used for various applications.
This blog provides an in-depth comparison of AWS DynamoDB vs Redis performance. It compares the data structure, architecture, durability, and usage cost of each of these databases. You can use this guide to decide which database aligns with your task objectives.