Cassandra vs DynamoDB – What’s the Difference. Businesses today aim at establishing large scale and distributed system based scalable databases. One of the most powerful databases that are available is Apache Cassandra and DynamoDB .
Firstly both Apache Cassandra and DynamoDB have great features for data storage technologies. They have numerous applications and are efficient at large scales. However, there are also differences that one must consider while deciding which database is the right solution for your application.
Apache Cassandra is an open-source database, while Amazon DynamoDB is a fully managed database service. Installation and configuration of Cassandra can be a bit challenging on comparing with Amazon DynamoDB.
On the other hand Amazon DynamoDB is accessible only through Amazon Web Services (AWS), whereas, developers using Cassandra can run the application anywhere. Firstly let us look at some of their features, benefits and then compare Cassandra vs DynamoDB – What’s the Difference.
What is Apache Cassandra?
Apache Cassandra is an open source, column oriented database with flexible data storage and distribution features. First of all the purpose to design the distributed database was to store and manage large data volumes across multiple data centers. Secondly, it serves real time operational data store and large scale business intelligence (BI) systems.
In addition it has a peer to peer architecture and allows developers to add multiple servers or nodes to the Cassandra cluster in any data center. Moreover the another feature of using Apache Cassandra is that it is fault tolerant, highly scalable and provides high availability.
What is more important to mention is that with the help of Apache Cassandra, developers can fast write large stored data without creating any impact on the read efficiency. It also allows developers to maintain a quick response time for each system.
To summarize its usage many high profile companies such as Apple, Facebook, Instagram, Twitter, eBay, Uber, Spotify, Netflix are currently using Cassandra, as it offers great benefits over other systems.
Features of Apache Cassandra
- It has flexible data storage and distribution features.
- Supports ACID
- Decentralized deployments.
- Multi Data Center Replication.
- Scalable and Consistent.
- Linear scalability.
- Fast linear scale performance.
- No Single point of failure.
- Restore and recovers failed nodes.
- Supports strong data consistency.
- Audit logging feature.
Pros of Apache Cassandra
- It allows users to store structured, semi structured and unstructured data. Further it supports easy data distribution.
- It allows users to manage high incoming data velocity.
- Cassandra is highly scalable and offers high availability
- Reduces downtime and data loss.
- Handles massive data volume across multiple servers.
- It allows developers to fast write data without creating any impact on the read efficiency.
- Fast, open source distribution database.
- Cassandra helps in maintaining a quick response time.
Cons of Apache Cassandra
- Do not support enough functions for computation on storage.
- Error in a single database will spread to other machines connected to the system.
What is DynamoDB?
On the other hand Amazon DynamoDB is a fully managed database service provided by Amazon Web Services. Firstly, it is a cost effective, highly available, scalable solution, best suitable for developers willing to design eCommerce scale data centric apps or in the gaming industry. Secondly it enables faster restoration of DynamoDB tables and supports streams to capture item level changes.
Thirdly, another feature that makes DynamoDB a better choice is the auto scaling feature. It is a key value and document oriented store database model that delivers consistently high performance at all scales.
In addition the developers do not have to worry about hardware provisioning, software patching, configuration and scaling with DynamoDB as it is fully managed by Amazon Web. Also DynamoDB provides in built security features, backup options, integration with AWS service, data export tools, automated multi region replication, unlimited throughput and storage.
Features of DynamoDB
- It supports streams to capture item level changes.
- Supports auto scaling.
- Secures data using Advanced Encryption Standard (AES-256).
- Data Export to Amazon S3 for analysis.
- Faster restoration of DynamoDB tables.
- Access using the Internet or AWS credentials.
- Supports property of distributed hash tables.
- The consistent reads are storing.
- Supports PartiQL for insertion, deleting, and updating DynamoDB tables.
- Allows real time replication of data.
- Unlimited throughput and storage.
- Supports automatic backup and restore features.
- Flexible schema.
- Integrates with other AWS services.
- DynamoDB Accelerator.
Pros of DynamoDB
- DynamoDB is easy to install and configure.
- It is a faster database compared to other relational database solutions.
- Developers can redesign applications using DynamoDB.
- Offers Consistent performance.
- Has a low learning curve.
- Allows access to the stream using an API call.
- Offers Fine Grained Access Control (FGAC) for data protection.
- Cost effective and can handle a large amount of data and request traffic.
- It allows exporting data to Amazon for analysis and extracting insights.
- The distributed database stores all the information in partitions.
Cons of DynamoDB
- DynamoDB has a weak querying model.
- The database lacks server side updates.
- Provisioned throughput and batch jobs fail to work together in DynamoDB
- Allows provisioning of its capacity at the entire table level
- Supports single region tables only.
- Requires developers to rebuild from an empty table to change or add replicas to an existing global table.
- Do not support traditional SQL server queries and access patterns.
- Poor documentation and not a good choice to store financial data.
- DynamoDB is available only in AWS. Users cannot run applications anywhere else.
- Improper configuration and management lead to security issues in the past.
Cassandra vs DynamoDB – What’s the Difference?
In summary from the above listed features, pros and cons, lets have a look at comparison of Cassandra vs DynamoDB – What’s the Difference from the parameters perspective.
Apache Cassandra vs AWS DynamoDB
| Parameters | Cassandra | DynamoDB |
|---|---|---|
|
Description |
Apache Cassandra is an open source distributed database that helps store and manage large data volume across multiple servers. |
DynamoDB is a fully managed distributed database provided by Amazon Web Services that can handle large amount of data and request traffic. |
|
Primary Database Model |
Apache Cassandra is a column oriented data store. |
It is a key value and document oriented store. |
|
Data Type |
The supported data type list is more extensive than DynamoDB. The list includes counter, timestamp, time, timeuuid, and uuid data types. |
It has the capability to store numerous data types. |
|
Attributes |
In Cassandra, partition keys and clustering columns allow more than one attribute. |
The partition keys and sort keys comprise only one attribute in the case of DynamoDB. |
|
Architecture |
Cassandra’s data distribution works based on consistent hashing and there are no hard limits for the number of tables. However, the practical limit is considered to be around 500 tables. |
DynamoDB data distribution works within one AWS region and has a limit of 256 number of tables. For more tables, one must reach out to AWS support. |
|
Item Size |
In Cassandra, the practical limit is a few megabytes and the hard limit is 2GB. |
400KB is the maximum size in DynamoDB. |
|
Operations |
Users may face operational overhead and challenges associated with deployments, updates, and patches. |
There is no stress about operations including configuration, hardware provisioning, and scaling. |
|
Provisioning |
Instance provisioning |
Not fixed |
|
Pricing |
Cost saving and writes are cheaper than reads. |
More complex with different models and pricing dimensions. |
|
Querying |
Querying data can be done with SQL like language. |
It uses proprietary API from AWS for Querying data. |
|
Portability |
Cassandra allows the users to run the application anywhere. |
DynamoDB is available only in AWS. Users cannot run applications anywhere else. |
|
Multi Region Functionality |
Adding a region to Cassandra is normal and fully operational. Thus, it provides strong consistency across multiple regions. |
Adding replicas to an existing global table requires uses to rebuild from an empty table. As a result, it provides eventual consistency across Global Tables. |
|
Type of License |
Open source |
Commercial |
|
Security features |
Offers client to node and inter node encryption |
Offers encryption at rest based on Advanced Encryption Standard (AES-256) |
|
Auto Scaling |
It does not support Auto Scaling |
Supports Auto Scaling |
|
Updates and Scanning |
Creates a mess when updating and scanning. |
Performs better Updates and Scanning. |
|
Scalability |
Linear Scalability |
Rapid Scalability |
|
Latency |
Extremely low Latency |
Relatively low LatencyUse Cases |
|
Use Cases |
Fraud detection, Messaging systems, etc. |
Real time bidding platforms, Gaming applications, etc. |
|
High Profile Companies |
Apple, Facebook, Instagram, Twitter, eBay, Uber, Spotify, Netflix, etc. are using Cassandra. |
Disney+, Zoom Video Communications, Inc., Capital One, Samsung, PayPay Corporation, Airbnb, etc. are using DynamoDB. |
Cassandra vs DynamoDB – What’s the Difference Conclusion
In conclusion the Cassandra and DynamoDB there are key differences such as
- The replication strategy
- The ownership (Database managed by you or AWS).
- The pricing model.
Furthermore both distributed databases have their pros and cons. DynamoDB supports auto scaling, comprises in built metrics for monitoring and encrypts data at rest. On the other hand, Cassandra offers fast writes, linear scalability, constant availability, reliable cross data center replication, and more benefits.
If you’re already using the AWS and require a NoSQL database then you should look into DynamoDB.
To summarize, the feature and technical issues should not be the only basis for comparing them. Follow the above listed features, benefits and disadvantages is to help you understand their structure and work to make the best choice for your company.
