DBMS > Apache Cassandra vs. MarkLogic vs. RDF4J vs. Teradata Aster

System Properties Comparison Apache Cassandra vs. MarkLogic vs. RDF4J 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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Operational and transactional Enterprise NoSQL database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Platform for big data analytics on multistructured data sources and types

Primary database model

Wide column store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

RDF store

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

cassandra.apache.org

www.progress.com/marklogic

rdf4j.org

Technical documentation

cassandra.apache.org/doc/latest

www.progress.com/marklogic/documentation

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

MarkLogic Corp.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Teradata

Initial release

2008

2001

2004

2005

Current release

5.0-rc1, July 2024

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

Schema can be enforced

yes

RDF Schemas

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

yes

SQL92

yes

APIs and other access methods

Proprietary protocol

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

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

Java
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

none

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

ACID

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Access rights for users can be defined per object

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

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

Apache 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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