Moving data from physical data centers to the cloud is a common practice among most organizations. Such a transition provides more flexibility, reduces costs, and allows you to scale your business operations as needed without maintaining the on-premise infrastructure.
Amazon S3 and DynamoDB are two notable cloud service choices for switching to the cloud. Both services enable you to utilize most of the cloud-native features fully. While S3 and DynamoDB enable you to store and manage large datasets, they differ in several key aspects. This article guides you to learn the key differences between Amazon S3 vs DynamoDB.
Amazon S3: A Brief Overview
Amazon S3 (Simple Storage Service) is a scalable, high-availability cloud-based object storage solution. It is built to store and manage large datasets across various applications, including websites, IoT devices, etc.
In Amazon S3, you can store data in buckets, which are containers that can hold large numbers of objects. Every object in the bucket has a key name that uniquely identifies it from other objects. After adding data to the bucket, you can retrieve information related to the objects, download it to your PC, copy it to another bucket, or delete your objects or buckets.
Key Features of Amazon S3
- S3 Versioning: With S3 versioning, you can maintain several versions of an object within a single bucket. This feature enables you to recover objects that might have been mistakenly altered or deleted.
- Robust Consistency: Amazon S3 offers robust read-after-write consistency for all applications without affecting performance or incurring additional costs. It ensures that after an object is written or modified, subsequent read requests will immediately retrieve the most recent version of that object.
- Access Management: By default, buckets and S3 objects are private. You can control access using AWS IAM policies, S3 access points, bucket policies, and access control lists.
- Storage Monitoring: Amazon S3 uses automated tools, like Amazon CloudWatch, which facilitates tracking the operational health of your S3 resources. You can also set billing notifications when the estimated charge reaches your limit.
Amazon DynamoDB: A Brief Overview
DynamoDB is a NoSQL key-value-based database service offered by Amazon. This fully managed solution serves more than one million customers, providing fast and scalable performance for applications of any size. It ensures your application can handle high-traffic loads with minimal latency.
In DynamoDB, you can store data in tables as items with attributes. To identify each item in the table, DynamoDB uses two primary keys: partition key and a combination of partition and sort keys.
Key Features of DynamoDB
- Auto Scaling: With DynamoDB’s auto-scaling feature, you can automatically adjust your table's read and write capacity when workloads increase, ensuring smooth performance. When traffic decreases, DynamoDB enables you to reduce the provisioned capacity, so you only pay for what you use.
- Multi-Region Replication: You can achieve multi-region replication using DynamoDB global tables; each table has several replicas in different AWS Regions. Since all replicas share the same name and primary key, DynamoDB updates all replicas when one is modified.
- Caching: DynamoDB supports Amazon DynamoDB Accelerator (DAX), a high-availability cache service. It allows you to add in-memory acceleration packages to your DynamoDB tables; you don’t have to manually deal with cache invalidation or data updates.
- Point-In-Time Recovery (PITR): PITR ensures your DynamoDB tables are secure against accidental writes or deletes. It helps you to automatically back up your table data of any size and restore data modified or deleted within the past 35 days.
Amazon S3 vs DynamoDB: What Are the Key Differences?
Now that you have explored basic S3 vs DynamoDB differences. Let’s take a look at the crucial aspects that differentiate both databases:
S3 vs DynamoDB Latency
Amazon S3 delivers high throughput with low latency for some of its storage classes. It is suitable for applications that manage large volumes of data. DynamoDB is also designed for fast, high-performance applications with low latency requirements, especially for smaller items under 4KB.
S3 vs DynamoDB Batch Operation
S3 Batch Operations helps you to execute large-scale operations such as copying, tagging, or deleting Amazon S3 objects. Conversely, DynamoDB uses API calls to perform batch writes, updates, and deletes within DynamoDB tables.
DynamoDB vs S3 Performance
Amazon S3 offers increased performance with up to 3,500 write requests per second and 5,500 retrieval requests per second per prefix in a bucket. This saves substantial time without additional costs. DynamoDB, on the other hand, facilitates 20 million requests per second with minimal database administration.
S3 vs DynamoDB Speed
S3 is optimized for high-throughput and large object storage. Its speed is influenced by factors like object size and network conditions. On the other hand, DynamoDB offers faster response times for small to medium-sized queries due to its in-memory caching and indexing. It is generally faster for real-time, high-speed data access.
Factors to Consider When Selecting Amazon S3 vs DynamoDB
Here are the main factors that influence the choice between Amazon S3 and DynamoDB:
Amazon S3 vs DynamoDB Challenges
Here are some challenges you must remember while choosing Amazon S3 or DynamoDB.
Challenges of S3
- Once you have created an S3 bucket, you cannot change its name and AWS Region.
- S3 has a request rate limit, and exceeding it can result in 503 Slow-down errors.
- S3 lacks in-built object locking for concurrent write operations, which can lead to data inconsistencies if multiple processes write to the same object simultaneously.
- You can load objects up to 5TB, but multipart uploads are required for files over 100 MB, which can be time-consuming.
Challenges of DynamoDB
- If your DynamoDB tables do not have a good partition key, it can result in uneven data distribution, causing throttling and slow performance.
- Creating secondary indexes that you do not query frequently increases storage and I/O costs.
- DynamoDB does not directly support table join operations like a relational database to handle data relationships and complex queries.
- DynamoDB transactions cannot have more than 4 MB of data and can only include up to 100 unique items.
Amazon DynamoDB vs S3 Cost
Pricing is another essential factor that helps you decide on the right database. Let’s explore the pricing information for both databases:
Pricing of S3
S3 costs are determined based on the usage of the following components:
- Storage Classes: Your charges depend on the storage class. Using the S3 Standard storage class for frequent data access would cost $0.023 per GB for the first 50 TB/month. For high-performance access to your most frequently accessed data, you can use S3 Express One Zone, which costs $0.16 per GB/month. The S3 Glacier Flexible Retrieval storage class would be beneficial at $0.0036 per GB/month to store long-term backups and archives with retrieval options.
- Data Transfer: After exhausting the 100GB free tier, you must pay $0.09 per GB for data transfer from S3 to a location outside the S3 region. There is no separate charge for all data transfers into S3.
- Storage Management: You are charged based on S3 Inventory, which costs $0.0025 per million objects, and S3 Object Tagging with $0.01 per 10,000 tags per month.
Pricing of DynamoDB
DynamoDB expenses are calculated according to the following two capacity modes:
- On-demand Capacity: In this capacity mode, you are charged $1.25 per million write request units and $0.25 per million read request units.
- Provisioned Capacity: This capacity mode charges you $0.00065 per write capacity unit and $0.00013 per read capacity unit.
DynamoDB bills additional charges for backup and restore global tables, change data capture, integration, and transfer.
Integrate Your Disparate Data With Amazon S3 and DynamoDB Using Airbyte
Your organizations must be generating vast amounts of data. To utilize the maximum potential of your organization’s data for analytical needs, consider aggregating all your data into a single destination, such as Amazon S3 and DynamoDB. Manually integrating data between these platforms is often time-consuming and requires extensive manual efforts.
To automate the migration process in minutes, consider using a data movement and replication platform like Airbyte. It offers 350+ pre-built connectors, including S3 and DynamoDB. These connectors allow you to transfer data from any source to S3 or DynamoDB or migrate S3 or DynamoDB data to your preferred destinations. You can even load all your data from Amazon S3 to DynamoDB for efficient querying.
Let’s understand some of the features of Airbyte:
- Custom Connector Development: If you cannot find the connector you’re looking for, Airbyte’s low-code Connector Development Kit (CDK) will help you create a custom one.
- Transformation with dbt: Data is spread across many sources, and it can be inconsistent. Airbyte and dbt integration help you standardize the data to avoid discrepancies and make it compatible with your destination system.
- Change Data Capture: New and unseen data might be generated in your operational database. Airbyte’s CDC approach allows you to specify a sync frequency to track the changes in the source system and replicate them to S3 or DynamoDB.
- Data Security: Airbyte uses TLS encryption, credential management, access control, and authentication modes to ensure that your data is secured. It also supports different compliance certifications such as ISO-270001, SOC 2 Type II, GDPR, and HIPAA.
- Vibrant Community: Airbyte is backed by a global community of developers, engineers, business analysts, and others who share their knowledge about data integration practices.
Conclusion
Amazon S3 and DynamoDB are two popular, cost-effective cloud storage options, each with unique advantages.
If you are looking for a NoSQL database solution, DynamoDB is an excellent choice, while S3 is suitable for large-scale object storage. For low-latency, real-time applications, DynamoDB works better than S3, but for handling unstructured data, S3 is ideal.
To determine your best fit, it is important to understand and assess your needs, selecting the one that aligns with your objectives.