Apache Cassandra

Website

cassandra.apache.org

$ Details

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Categories

#Databases #NoSQL Databases #Relational Databases #Big Data

vert.x

Website

vertx.io

$ Details

Categories

#Web Frameworks #Developer Tools #PHP MVC Framework #Runtime

Apache Cassandra features and specs

• Scalability
  Apache Cassandra is designed for linear scalability and can handle large volumes of data across many commodity servers without a single point of failure.
• High Availability
  Cassandra ensures high availability by replicating data across multiple nodes. Even if some nodes fail, the system remains operational.
• Performance
  It provides fast writes and reads by using a peer-to-peer architecture, making it highly suitable for applications requiring quick data access.
• Flexible Data Model
  Cassandra supports a flexible schema, allowing users to add new columns to a table at any time, making it adaptable for various use cases.
• Geographical Distribution
  Data can be distributed across multiple data centers, ensuring low-latency access for geographically distributed users.
• No Single Point of Failure
  Its decentralized nature ensures there is no single point of failure, which enhances resilience and fault-tolerance.

Possible disadvantages of Apache Cassandra

• Complexity
  Managing and configuring Cassandra can be complex, requiring specialized knowledge and skills for optimal performance.
• Eventual Consistency
  Cassandra follows an eventual consistency model, meaning that there might be a delay before all nodes have the latest data, which may not be suitable for all use cases.
• Write-heavy Operations
  Although Cassandra handles writes efficiently, write-heavy workloads can lead to compaction issues and increased read latency.
• Limited Query Capabilities
  Cassandra's query capabilities are relatively limited compared to traditional RDBMS, lacking support for complex joins and aggregations.
• Maintenance Overhead
  Regular maintenance tasks such as node repair and compaction are necessary to ensure optimal performance, adding to the administrative overhead.
• Tooling and Ecosystem
  While the ecosystem for Cassandra is growing, it is still not as extensive or mature as those for some other database technologies.

vert.x features and specs

• Performance
  Vert.x is designed to be highly performant, leveraging a non-blocking, event-driven architecture which makes it suitable for handling many concurrent requests efficiently.
• Polyglot
  Vert.x supports multiple programming languages, including Java, Kotlin, JavaScript, Groovy, Ruby, and more. This allows developers to use the language they are most comfortable with.
• Modular
  Vert.x is modular and lightweight, enabling developers to use only the parts they need and easily integrate with other libraries and tools.
• Reactive Ecosystem
  Vert.x provides a robust ecosystem for building reactive applications, including asynchronous APIs, event bus, and reactive streams.
• Scalability
  The architecture of Vert.x allows for easy scaling both vertically and horizontally, as it can efficiently manage resources and load balancing.

Possible disadvantages of vert.x

• Learning Curve
  The event-driven and asynchronous nature of Vert.x can be challenging for developers who are accustomed to traditional synchronous programming paradigms.
• Community and Resources
  While growing, the Vert.x community is smaller compared to more established frameworks, which may result in fewer resources, tutorials, and third-party integrations.
• Complexity
  As applications grow in size, managing asynchronous code and callback structures can become complex, requiring careful planning and architecture decisions.
• Tooling
  Tooling support, while improving, may not be as comprehensive as other established frameworks, which might impact development speed and debugging.

Course Intro | DS101: Introduction to Apache Cassandra™

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