DBMS > MarkLogic vs. SiteWhere vs. Teradata Aster

System Properties Comparison MarkLogic vs. SiteWhere vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Operational and transactional Enterprise NoSQL database

M2M integration platform for persisting/querying time series data

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Time Series DBMS

Relational DBMS

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

Score	6.50
Rank	#56	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#5	Search engines

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

www.marklogic.com

github.com/sitewhere/sitewhere

Technical documentation

docs.marklogic.com

sitewhere1.sitewhere.io/index.html

Developer

MarkLogic Corp.

SiteWhere

Teradata

Initial release

2001

2010

2005

Current release

11.0, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Common Public Attribution License Version 1.0

commercial

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.

Implementation language

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Data scheme

schema-free

Schema can be enforced

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

APIs and other access methods

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

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

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, with Range Indexes

User concepts

Access control

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

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