apache/cassandra

Features

• NoSQL Databases - Provides a distributed NoSQL database designed for high availability and linear scalability of structured data.
• Wide-Column Stores - Provides a wide-column store data model with a flexible schema based on rows and primary keys.
• Data Access and Querying - Provides a CQL-compliant interface for querying structured tabular data organized in rows and columns.
• Data Partitioning - Automatically spreads tabular data across multiple machines to ensure linear scalability and avoid single points of failure.
• Data Replication Strategies - Implements quorum-based replication to balance data consistency and fault tolerance across distributed nodes.
• Tabular Row Storage - Organizes information into rows and columns using primary keys and a structured query language.
• Distributed Consensus Stores - Maintains a distributed data store designed to eliminate single points of failure across multiple servers.
• CQL Interfaces - Uses a structured query language (CQL) to manage and retrieve data from distributed tables.
• Data Partitioning - Automatically partitions data across multiple servers to maintain transparency and scalability during cluster changes.
• Fault Tolerant Storage - Replicates data across multiple nodes to ensure the system remains operational during hardware or software failures.
• High-Volume Tabular Querying - Uses a standardized query language to retrieve and manage structured tabular information at scale.
• Horizontal Database Scaling - Enables horizontal database scaling by adding new nodes to the cluster without interrupting active services.
• Log-Structured Merge-Trees - Utilizes a log-structured merge-tree storage engine to optimize write throughput via immutable memory tables.
• Gossip Protocols - Employs a gossip protocol for peer-to-peer propagation of cluster membership and node health state.
• Consistent Hashing - Uses consistent hashing to distribute data across a ring of nodes, enabling linear scalability.
• Distributed Data Management - Manages the storage and retrieval of large datasets across a cluster of servers for high availability.
• Data Snapshotting - Supports creating system snapshots of data files for rapid recovery or rollbacks before upgrades.
• Data Transformation Functions - Supports the execution of user-defined functions for complex data transformations and specialized calculations.
• Sorted String Tables - Stores data in sorted string tables that remain immutable and are periodically merged via compaction.
• Server Configuration - Provides a central configuration file to manage operational parameters and system resource behavior.
• Write-Ahead Logging - Implements a commit log to ensure all mutations are persisted to disk before memory updates for crash recovery.
• Cluster Integration Testing - Implements cluster tests using fault injection and lifecycle management to verify correctness across multiple nodes.
• Time-To-Live Expirations - Supports time-to-live (TTL) durations for records to automate data expiration and removal.
• Database Engines - Partitioned row store for distributed data management.
• Database Management Systems - Highly scalable distributed NoSQL database system.
• Database Systems - Scalable, distributed NoSQL database.
• Data Engineering - Scalable distributed NoSQL database for large data.

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