DBMS > Dgraph vs. Ehcache vs. MarkLogic vs. MonetDB vs. Oracle

System Properties Comparison Dgraph vs. Ehcache vs. MarkLogic vs. MonetDB vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

A widely adopted Java cache with tiered storage options

Operational and transactional Enterprise NoSQL database

A relational database management system that stores data in columns

Widely used RDBMS

Primary database model

Graph DBMS

Key-value store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.oracle.com/database

Technical documentation

dgraph.io/docs

www.ehcache.org/documentation

docs.marklogic.com

www.monetdb.org/Documentation

docs.oracle.com/en/database

Developer

Dgraph Labs, Inc.

Terracotta Inc, owned by Software AG

MarkLogic Corp.

MonetDB BV

Oracle

Initial release

2016

2009

2001

2004

1980

Current release

3.10.0, March 2022

11.0, December 2022

Dec2023 (11.49), December 2023

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

commercial

restricted free version is available

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

Java

C++

C and C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

Schema can be enforced

yes

Schemaless in JSON and XML columns

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

SQL 2003 with some extensions

yes

with proprietary extensions

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JCache

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Java

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

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes, in SQL, C, R

PL/SQL

also stored procedures in Java possible

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

by using Terracotta Server

Sharding

Sharding via remote tables

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

by using Terracotta Server

yes

none

Source-replica replication available in experimental status

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

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

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Planned for future releases

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

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