DBMS > DolphinDB vs. Graph Engine vs. OrientDB vs. RDF4J vs. TimesTen

System Properties Comparison DolphinDB vs. Graph Engine vs. OrientDB vs. RDF4J vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

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

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Document store
Graph DBMS
Key-value store

RDF store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.graphengine.io/docs/manual

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

rdf4j.org/documentation

docs.oracle.com/database/timesten-18.1

Developer

DolphinDB, Inc

Microsoft

OrientDB LTD; CallidusCloud; SAP

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

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2010

2004

1998

Current release

v2.00.4, January 2022

3.2.29, March 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

Open Source

Apache version 2

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.

Implementation language

C++

.NET and C

Java

Server operating systems

Linux
Windows

.NET

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

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

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

yes

RDF Schemas

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C#
C++
F#
Visual Basic

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

Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Java, Javascript

yes

PL/SQL

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

yes

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

in-memory storage is supported as well

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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21 January 2014, Matthias Gelbmann

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