DBMS > Alibaba Cloud Table Store vs. MarkLogic vs. MySQL vs. TimesTen

System Properties Comparison Alibaba Cloud Table Store vs. MarkLogic vs. MySQL vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Wide column store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.marklogic.com

www.mysql.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.marklogic.com

dev.mysql.com/doc

docs.oracle.com/database/timesten-18.1

Developer

Alibaba

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2001

1995

1998

Current release

11.0, December 2022

8.4.0, April 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

Schema can be enforced

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

with proprietary extensions

yes

APIs and other access methods

HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

proprietary syntax

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-row operations

ACID

can act as a resource manager in an XA/JTA transaction

ACID

not for MyISAM storage engine

ACID

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes, with Range Indexes

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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