Apache Cassandra

Website

cassandra.apache.org

Pricing URL

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$ Details

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Categories

#Databases #NoSQL Databases #Relational Databases #Big Data

Raven DB

Website

ravendb.net

Pricing URL

Official Raven DB Pricing

$ Details

Categories

#MySQL Tools #Data Analysis #Database Management #MySQL GUI

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.

Raven DB features and specs

• Schema-less Design
  RavenDB offers a schema-less document database structure, allowing for flexible data modeling where you can easily evolve your data model over time without the need for complex migrations.
• ACID Transactions
  The database supports ACID transactions, ensuring consistent and reliable operations across multiple documents, which is beneficial for applications that require strong data consistency.
• Built-in Indexing
  RavenDB includes automatic indexing as well as customizable indexing options, which provide efficient querying capabilities and enhance performance without requiring extensive setup.
• Replication and Sharding
  It supports replication and sharding, enabling horizontal scaling and high availability, which are crucial for large-scale applications requiring distributed data across servers.
• Ease of Use
  RavenDB offers an intuitive management interface and APIs, making it user-friendly and allowing developers to quickly integrate it into projects without steep learning curves.

Possible disadvantages of Raven DB

• Limited Ecosystem
  Compared to more mature databases, RavenDB might have a smaller ecosystem of plugins and third-party tools, which could limit its integration possibilities with other technologies.
• Cost
  While there is an open-source version, accessing the full range of enterprise features in RavenDB might require a commercial license, potentially increasing costs for small projects or startups.
• Community Support
  Being a relatively niche database compared to giants like MongoDB or PostgreSQL, it has a smaller community, which could mean fewer community-driven resources or solutions.
• Learning Curve
  Developers accustomed to SQL databases might find the transition to a document-based database like RavenDB challenging, necessitating time spent learning new paradigms and practices.
• Performance Trade-offs
  While RavenDB offers great flexibility and powerful features, certain workloads might experience performance trade-offs, particularly if not optimized or configured correctly for specific use cases.

Course Intro | DS101: Introduction to Apache Cassandra™

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