DBMS > Apache Cassandra vs. IRONdb vs. openGauss vs. Riak TS

System Properties Comparison Apache Cassandra vs. IRONdb vs. openGauss vs. Riak TS

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.11
Rank	#175	Overall
	#79	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

cassandra.apache.org

www.circonus.com/solutions/time-series-database/

gitee.com/opengauss
opengauss.org

Technical documentation

cassandra.apache.org/doc/latest

docs.circonus.com/irondb/category/getting-started

docs.opengauss.org/en
gitee.com/opengauss/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Circonus LLC.

Huawei and openGauss community

Open Source, formerly Basho Technologies

Initial release

2008

2017

2019

2015

Current release

5.0-rc1, July 2024

V0.10.20, January 2018

3.0, March 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C and C++

C, C++, Java

Erlang

Server operating systems

BSD
Linux
OS X
Windows

Linux

Linux
OS X

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

restricted

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

SQL-like query language (Circonus Analytics Query Language: CAQL)

ANSI SQL 2011

yes, limited

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

HTTP API

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes, in Lua

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Automatic, metric affinity per node

horizontal partitioning (by range, list and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

configurable replication factor, datacenter aware

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users can be defined per object

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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