Apache Cassandra

Website

cassandra.apache.org

Categories

#Databases #NoSQL Databases #Relational Databases #Big Data

Bitsy

Website

bitbucket.org

Categories

#Graph Databases #Databases #NoSQL Databases #Game Engine

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.

Bitsy features and specs

• Lightweight
  Bitsy is a small and simple graph database designed for lightweight uses, which makes it easier to deploy and integrate without the overhead of larger databases.
• ACID Transactions
  It offers ACID-compliant transactions, ensuring data integrity and consistency, which is crucial for applications requiring reliable transactional support.
• Java Integration
  It is implemented in Java, which allows seamless integration with Java applications and easy embedding within Java projects.
• Embedded Usage
  Bitsy can be embedded directly into an application, meaning it can run in the same process as the application, often leading to performance benefits.

Possible disadvantages of Bitsy

• Limited Features
  Compared to larger graph databases, Bitsy lacks advanced features such as extensive analytics, scalability options, or graph algorithms, limiting its use for complex tasks.
• Community and Support
  Being a smaller project, the community around Bitsy is not as large or active as those around more widely-used graph databases, which can lead to challenges in finding support and resources.
• Scalability
  Bitsy is not designed for large-scale graph database uses, which can be a limitation for applications that expect to grow significantly in data volume or require distributed database solutions.
• Limited Language Support
  As a Java-based database, it may not offer the same level of support or ease of integration with non-Java environments compared to language-agnostic databases.

Course Intro | DS101: Introduction to Apache Cassandra™

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