DBMS > DolphinDB vs. Graph Engine vs. HugeGraph vs. Linter vs. OushuDB

System Properties Comparison DolphinDB vs. Graph Engine vs. HugeGraph vs. Linter vs. OushuDB

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

A fast-speed and highly-scalable Graph DBMS

RDBMS for high security requirements

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Graph DBMS

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

www.dolphindb.com

www.graphengine.io

github.com/hugegraph
hugegraph.apache.org

linter.ru

www.oushu.com/product/oushuDB

Technical documentation

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

www.graphengine.io/docs/manual

hugegraph.apache.org/docs

www.oushu.com/documentation

Developer

DolphinDB, Inc

Microsoft

Baidu

relex.ru

Oushu

Initial release

2018

2010

2018

1990

Current release

v2.00.4, January 2022

0.9

4.0.1, August 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

Open Source

Apache Version 2.0

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

C and C++

Server operating systems

Linux
Windows

.NET

Linux
macOS
Unix

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

Data scheme

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

yes

Full-featured ANSI SQL support

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

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

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

C#
C++
F#
Visual Basic

Groovy
Java
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C++

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes

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 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

Users, roles and permissions

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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