DBMS > Altibase vs. Apache Impala vs. Cassandra vs. MySQL vs. STSdb

System Properties Comparison Altibase vs. Apache Impala vs. Cassandra vs. MySQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Analytic DBMS for Hadoop

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Widely used open source RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store

Vector DBMS

starting with release V5

Document store
Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

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

impala.apache.org/impala-docs.html

cassandra.apache.org/doc/latest

dev.mysql.com/doc

Developer

Altibase

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top level project, originally developped by Facebook

Oracle

since 2010, originally MySQL AB, then Sun

STS Soft SC

Initial release

1999

2013

2008

1995

2011

Current release

v7.3, 2023, August 2023

4.1.0, June 2022

4.1.3, July 2023

8.4.0, April 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Java

C and C++

Server operating systems

AIX
HP-UX
Linux

Linux

BSD
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

ANSI SQL-92

SQL-like DML and DDL statements

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

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Proprietary protocol

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

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per object

Users with fine-grained authorization concept

no user groups or roles

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...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

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