Dynamodb Vs Cassandra: Pros and Cons – Which is Better?

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In this article, we will discuss cassandra db vs dynamodb, the difference between them and the pros and cons.

Dynamodb Vs Cassandra: Pros and Cons – Which is Better?

Introduction to Dynamodb

Amazon DynamoDB is a key-value-focused NoSQL database that is native to the cloud. Let’s clarify each of those phrases.

  • In order to function on Amazon Web Services, DynamoDB must be cloud-native, meaning it cannot run on-premises or even in a hybrid cloud (AWS). This makes it possible to scale as necessary without forcing a customer to make a large hardware investment. It also has characteristics with other cloud-native applications, like flexible technology infrastructure. It means that as you request more capacity, AWS will proactively provision new servers.
  • Because ANSI Structured Query Language is not supported by DynamoDB, it is a NoSQL database (SQL). As an alternative, it makes use of a private API built on Object Notation in JavaScript (JSON). The AWS Software Developer Kits (SDKs) to DynamoDB are created in a variety of programming languages, including C++, Go, Java, JavaScript, Microsoft.NET, Node.js, PHP, Python, and Ruby. This API is typically not required in order by user developers instead it is invoked through these SDKs.
  • Insofar as its data model is composed of key-value pairs in a very huge, non-relational database of rows with no schema, DynamoDB is largely a key-value store (records). Using foreign keys to join tables is not supported by systems for managing relational databases (RDBMS). JavaScript Object Notation can be used to handle a content store data model (JSON).

Also Read: Data Visualization In Python

Benefits of Dynamodb

  1. Users can make use of DynamoDB’s almost limitless storage as needed. Additionally, it gives developers the freedom to extend the database only when the application begins to gather data rather than right away. Therefore, when deploying the database, reserve storage is not required.
  2. DynamoDB duplicates table data by default over three availability zones in a single region. You can simply recover from any calamity and prevent service interruptions thanks to it.
  3. Users of the DynamoDB NoSQL database service are not required to manage any underlying infrastructures because it is fully managed. Users may instead concentrate on creating their applications thanks to this. AWS manages time-consuming operations like database upgrades, high availability, and sometimes even managing the infrastructure within its data centres.
  4. The DynamoDB storage service adheres to numerous internationally known regulatory compliance standards including PCI DSS, HIPAA, and NIST while providing explicit, demonstrated security rules.
  5. The solitary response times of DynamoDB are among its most frequently mentioned benefits. These reaction times are important since DynamoDB guarantees instantaneous responses at any scale.

Disadvantages of Dynamodb

  1. Despite the fact that DynamoDB can store a lot of data, the service’s restricted querying tools make it difficult to query data from DynamoDB databases.
  2. Although the on-demand approach’s flexibility enables seamless expansion, one of the major disadvantages of employing this strategy is its unpredictability and high costs.
  3. The possibilities for querying the data in DynamoDB’s tables are restricted, and the severity of the queries is also constrained.
  4. Similar to the restrictions placed on each item size inside a DynamoDB table, DynamoDB imposes restrictions on the majority of its components. The maximum size for an entry is 400KB, and it’s important to remember that users cannot in any manner increase this figure.

Introduction to Cassandra

Apache Cassandra is a freely available, distributed, and fragmented storage system (database) for managing extremely huge amounts of structured data dispersed throughout the world. No single point of failure is present, and it offers highly available service.

A few key points are listed below.

  • It is consistent, fault-tolerant, and scalable.
  • It is a database that is column-oriented.
  • Its data model is built on Google’s Big Table, while its distribution strategy is based on Amazon’s Dynamo.
  • It is distinct from relational database management systems and was developed at Facebook.
  • Cassandra offers a more potent “column family” data model while implementing a replication approach a la Dynamo with no single failure point.
  • Some of the most well-known businesses, like Facebook, Twitter, Cisco, Rackspace, eBay, Twitter, Netflix, and more, use Cassandra.

Advantages of Cassandra

  1. Because Cassandra is so highly scalable, new hardware can be added as needed to handle more customers and data.
  2. For applications that are business-critical and cannot afford failure, Cassandra has no single failure point and is always available.
  3. Because Cassandra is linearly scalable, your throughput rises as the number of cluster nodes rises. As a result, it keeps a short response time.
  4. Cassandra accommodates all possible data formats including structured, semi-structured, and unstructured. It can dynamically accommodate changes to your data structures according to your need.
  5. Cassandra offers flexibility in data distribution by duplicating data across many data centers.
  6. Properties like Data integrity, Stability, Isolation, and Durability are supported by Cassandra (ACID).
  7. Cassandra was created to operate on low-cost, common hardware. It can store bulky data without degrading read efficiency.
  8. Always on architecture

Disadvantages of Cassandra

No database management tool is flawless, of course. Here are some drawbacks of Cassandra:

  1. Relational data characteristics including ACID are not supported.
  2. Transactions take longer because of how much data and requests it manages, which causes latency problems.
  3. Because data is modeled more after searches than after structure, the same information is frequently retained.
  4. Cassandra holds a lot of data, so there may be problems with JVM memory management.
  5. There is no support for joins or subqueries.
  6. Aggregates are not supported by Cassandra.
  7. Reading has a tendency to be slower because Cassandra was designed from the outset for quick writing.
  8. Last but not least, there is no official documentation from Apache, thus you must search among independent businesses.

Difference between Dynamodb and Cassandra (Pros and Cons)

Basic db modelcolumn-oriented data store.document-oriented store
Data typescounter, timestamp, time, timeuuid, and UUIDstore various data types
Features – attributesCassandra was designed from the beginning to provide quick writes, and reads using partition keys, and clustering columns with multiple attribute support.With DynamoDB, the partition keys and sort keys are combined into a single property.
Item SizeLimited to 2GBLimited to 400kb
ScalabilityOffers linear scalabilityOffers exponential scalability
Latency rateLowhigh
QueryingWith a language similar to SQL, data queries can be made.For data querying, it makes use of AWS’s proprietary API.

How Dynamodb and Cassandra are related?

The same paper is where Cassandra and DynamoDB both come from: Dynamo: the Highly Available Key-Value Store on Amazon.com. A significant portion of Dynamo’s differences from Cassandra come from the latter’s key-value store data model. Cassandra is also built to be a column-family data storage.

Is Cassandra Similar to DynamoDB?

Comparing AWS DynamoDB vs Apache Cassandra. A distributed open-source database called Apache Cassandra is useful for storing and managing a lot of data across several servers. The distributed database DynamoDB, which is fully managed and offered by Amazon Web Services, can manage high volumes of data and request traffic.

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