Apache Cassandra

Website

cassandra.apache.org

Categories

#Databases #NoSQL Databases #Relational Databases #Big Data

Redis Enterprise

Website

redis.io

Categories

#Databases #Graph Databases #NoSQL Databases #Big Data

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.

Redis Enterprise features and specs

• Performance
  Redis Enterprise is known for its high performance in terms of speed and low latency, making it suitable for applications that require real-time processing.
• Scalability
  The platform offers linear scalability, enabling seamless growth by adding more nodes to handle increasing workloads.
• Persistence
  Provides multiple data persistence options, allowing businesses to choose how they save data according to their needs.
• Multi-model capability
  Supports multiple data models like time-series, graph, and JSON, making it versatile for various use cases.
• High Availability
  Redis Enterprise offers strong high availability features, including automated failover and data replication across geographic locations.
• Extensibility
  Through modules and custom commands, Redis Enterprise allows users to extend and customize its capabilities.

Possible disadvantages of Redis Enterprise

• Cost
  Redis Enterprise can be expensive for some organizations, particularly for small businesses or projects with limited budgets.
• Complexity
  The myriad of features and options might introduce complexity, requiring skilled personnel to manage and deploy effectively.
• Limited to in-memory storage
  While Redis provides persistence options, it primarily operates in-memory, which may not be suitable for all data sets or sizes.
• Vendor lock-in
  Utilizing Redis Enterprise-specific features may lead to vendor lock-in, making it difficult to switch to other solutions in the future.
• Learning curve
  New users may face a learning curve due to the various advanced features and configurations available in Redis Enterprise.

Course Intro | DS101: Introduction to Apache Cassandra™

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