DBMS > Cachelot.io vs. eXtremeDB vs. Hawkular Metrics vs. MarkLogic vs. RDF4J

System Properties Comparison Cachelot.io vs. eXtremeDB vs. Hawkular Metrics vs. MarkLogic vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Natively in-memory DBMS with options for persistency, high-availability and clustering

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Operational and transactional Enterprise NoSQL database

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

Primary database model

Key-value store

Relational DBMS
Time Series DBMS

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

RDF store

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

Technical documentation

www.mcobject.com/docs/extremedb.htm

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.marklogic.com

rdf4j.org/documentation

Developer

McObject

Community supported by Red Hat

MarkLogic Corp.

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

Initial release

2015

2001

2014

2001

2004

Current release

8.2, 2021

11.0, December 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

C and C++

Java

C++

Java

Server operating systems

FreeBSD
Linux
OS X

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

yes

RDF Schemas

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

SQL92

APIs and other access methods

Memcached protocol

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

HTTP REST

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

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Java
Lua
Python
Scala

Go
Java
Python
Ruby

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

Triggers

yes

by defining events

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor

based on Cassandra

yes

none

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

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

yes, with Range Indexes

User concepts

Access control

Role-based access control at the document and subdocument levels

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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