Apache Cassandra

Website

cassandra.apache.org

$ Details

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Categories

#Databases #NoSQL Databases #Relational Databases #Big Data

Knex.js

Website

knexjs.org

$ Details

Categories

#Database Management #MySQL Tools #Database Tools #Databases

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.

Knex.js features and specs

• SQL Query Builder
  Knex.js provides a flexible and powerful SQL query builder that allows developers to create complex queries using a fluent, chainable API. This can make writing and maintaining SQL queries simpler and more intuitive.
• Database Agnostic
  Knex.js supports multiple database systems such as PostgreSQL, MySQL, SQLite3, Oracle, and others. This makes it easier to switch between different databases without changing the application code.
• Promise-based API
  Its promise-based API allows for better handling of asynchronous operations and more readable code, making it easier to work with Node.js’s asynchronous nature.
• Migration Tooling
  Knex.js comes with built-in migration support, enabling developers to version and manage database schema changes in a structured manner.
• Active Development & Community
  Knex.js has a strong community and is actively maintained, ensuring regular updates, bug fixes, and continuous improvement.

Possible disadvantages of Knex.js

• Learning Curve
  While the chainable API is powerful, it can be slightly difficult for newcomers to grasp initially, especially if they are not familiar with fluent interfaces.
• Verbose Syntax
  Some developers might find the syntax to be more verbose compared to raw SQL or other query builders, leading to longer code for complex queries.
• Limited ORM Features
  Knex.js is a query builder, not a full-fledged Object-Relational Mapper (ORM). It lacks some advanced ORM features like object lifecycle management, caching, and entity relationships, which some developers may need.
• Inconsistent Documentation
  Though generally well-documented, some parts of Knex.js’s documentation can be incomplete or inconsistent, making it harder to find detailed information on advanced usage.
• Complexity in Complex Queries
  For more complicated queries, the chainable methodology can make the query construction cumbersome and error-prone, potentially leading to more debugging and maintenance overhead.

Course Intro | DS101: Introduction to Apache Cassandra™

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