Apache Cassandra

Website

cassandra.apache.org

Categories

#Databases #NoSQL Databases #Relational Databases #Big Data

BoltDB

Website

github.com

Categories

#NoSQL Databases #Databases #Key-Value Database #Graph 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.

BoltDB features and specs

• Simplicity
  BoltDB is easy to use with a simple API, making it accessible for developers to integrate into applications without a steep learning curve.
• Performance
  Designed for high read performance, BoltDB offers efficient access to data that makes it suitable for applications with heavy read workloads.
• ACID Transactions
  BoltDB supports ACID transactions, ensuring data integrity and reliability across operations, which is essential for applications that require consistent state.
• Embedded
  As an embedded key/value store, BoltDB operates within the application's memory space, reducing the overhead associated with server-based databases.
• Go-centric
  Written in pure Go, BoltDB is optimized for applications written in Go, providing seamless integration and compatibility for Go developers.

Possible disadvantages of BoltDB

• Write Concurrency
  BoltDB uses a single writer with multiple readers, which can become a bottleneck in write-heavy applications as concurrent writes are not supported.
• Scalability
  Designed as an embedded database, BoltDB is not ideal for applications requiring distributed or highly scalable database solutions.
• Deprecation
  BoltDB is no longer actively maintained in its original repository, which may deter developers from adopting it due to potential risks with unsupported software.
• Large Dataset Handling
  BoltDB might experience performance degradation with very large datasets, as it was primarily designed for smaller, single-node applications.
• Limited Features
  Compared to more advanced databases, BoltDB lacks features like advanced querying capabilities, caching mechanisms, and complex data types that might be needed in complex applications.

Analysis of Apache Cassandra

Course Intro | DS101: Introduction to Apache Cassandra™

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