DBMS > Dgraph vs. MarkLogic vs. Oracle Berkeley DB vs. OrientDB

System Properties Comparison Dgraph vs. MarkLogic vs. Oracle Berkeley DB vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Operational and transactional Enterprise NoSQL database

Widely used in-process key-value store

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Graph DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Graph DBMS
Key-value store

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

dgraph.io

www.marklogic.com

www.oracle.com/database/technologies/related/berkeleydb.html

orientdb.org

Technical documentation

dgraph.io/docs

docs.marklogic.com

docs.oracle.com/cd/E17076_05/html/index.html

www.orientdb.com/docs/last/index.html

Developer

Dgraph Labs, Inc.

MarkLogic Corp.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

OrientDB LTD; CallidusCloud; SAP

Initial release

2016

2001

1994

2010

Current release

11.0, December 2022

18.1.40, May 2020

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

commercial license available

Open Source

Apache version 2

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, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

Schema can be enforced

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

SQL interfaced based on SQLite is available

SQL-like query language, no joins

APIs and other access methods

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

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

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

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

Java, Javascript

Triggers

yes

only for the SQL API

Hooks

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

yes

User concepts

Access control

Planned for future releases

Role-based access control at the document and subdocument levels

Access rights for users and roles; record level security configurable

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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