DBMS > Altibase vs. Cassandra vs. Citus vs. Ignite

System Properties Comparison Altibase vs. Cassandra vs. Citus vs. Ignite

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Document store

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cassandra.apache.org/doc/latest

docs.citusdata.com

apacheignite.readme.io/docs

Developer

Altibase

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation

Initial release

1999

2008

2010

2015

Current release

v7.3, 2023, August 2023

4.1.3, July 2023

8.1, December 2018

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache version 2

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0

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

C++

Java

C++, Java, .Net

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

ANSI SQL-92

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

yes

standard, with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Proprietary protocol

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C
C++
Java

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

other methods possible by using 3rd party extensions

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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

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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