Overview
Apache Cassandra is an open-source, distributed NoSQL database. It implements a partitioned wide-column storage model with eventually consistent semantics.
Cassandra was created at Facebook using a staged event-driven architecture (SEDA). This initial design implemented a combination of Amazon’s Dynamo distributed storage and replication techniques and Google’s Bigtable data and storage engine model. Dynamo and Bigtable were both developed to meet emerging requirements for scalable, reliable and highly available storage systems, but each had areas that could be improved.
Apache Cassandra was designed to combine the strengths of both of these distributed database systems to address scalability, both in terms of data volume and query throughput. As applications increasingly demanded global replication, continuous availability, and low-latency reads and writes, a new database model became necessary, one that traditional relational systems of the time were not well suited to support.
Apache Cassandra was created to meet these challenges with the following design objectives:
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Full multi-primary database replication
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Global availability at low latency
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Scaling out on commodity hardware
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Linear throughput increase with each additional processor
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Online load balancing and cluster growth
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Partitioned key-oriented queries
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Flexible schema
Features
Cassandra provides the Cassandra Query Language (CQL), an SQL-like language, to create, modify, and delete database schema, as well as access data. CQL allows users to organize data within a cluster of Cassandra nodes using:
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Keyspace: Specifies the replication strategy for a dataset across different datacenters. Replication refers to the number of copies stored within a cluster. Keyspaces serve as containers for tables.
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Table: Tables are composed of rows and columns. Columns define the typed schema for a single datum in a table. Tables are partitioned based on the columns provided in the partition key. Cassandra tables can flexibly add new columns to tables with zero downtime.
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Partition Key: The required component of the primary key that determines which node in the Cassandra cluster stores a given row. For efficient execution, queries must include the partition key.
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Row: Contains a collection of columns identified by a unique primary key made up of the partition key and optionally additional clustering keys.
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Column: A single datum with a type which belongs to a row.
CQL supports numerous advanced features over a partitioned dataset such as:
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Collection types including sets, maps, and lists
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User-defined types, tuples, functions and aggregates
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Storage-attached indexing (SAI) for secondary indexes
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Local secondary indexes (2i)
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User-defined types, functions and aggregates
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Single-partition lightweight transactions with atomic compare and set semantics
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(Experimental) materialized views
Cassandra explicitly chooses not to implement operations that require cross-partition coordination as they are typically slow and hard to provide highly available global semantics. For example, Cassandra does not support:
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Cross-partition transactions
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Distributed joins
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Foreign keys or referential integrity.
Operating
Apache Cassandra configuration settings are configured in the cassandra.yaml file that can be edited by hand or with the aid of configuration management tools.
Some settings can be manipulated live using an online interface, but others require a restart of the database
to take effect.
Cassandra provides tools for managing a cluster.
The nodetool command interacts with Cassandra’s live control interface, allowing runtime
manipulation of many settings from cassandra.yaml.
The auditlogviewer is used to view the audit logs.
The fqltool is used to view, replay and compare full query logs.
In addition, Cassandra supports out of the box atomic snapshot functionality, which presents a point in time (PIT) snapshot of Cassandra’s data for easy integration with many backup tools. Cassandra also supports incremental backups where data can be backed up as it is written.
