DBMS > Amazon Redshift vs. MarkLogic vs. Teradata Aster vs. Warp 10

System Properties Comparison Amazon Redshift vs. MarkLogic vs. Teradata Aster vs. Warp 10

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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

Large scale data warehouse service for use with business intelligence tools

Operational and transactional Enterprise NoSQL database

Platform for big data analytics on multistructured data sources and types

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

www.marklogic.com

www.warp10.io

Technical documentation

docs.aws.amazon.com/redshift

docs.marklogic.com

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

MarkLogic Corp.

Teradata

SenX

Initial release

2012

2001

2005

2015

Current release

11.0, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

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

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

schema-free

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL92

yes

APIs and other access methods

JDBC
ODBC

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
OLE DB

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via XQuery or JavaScript

R packages

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

yes, with Range Indexes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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