DBMS > DolphinDB vs. JanusGraph vs. Newts

System Properties Comparison DolphinDB vs. JanusGraph vs. Newts

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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 Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Time Series DBMS based on Cassandra

Primary database model

Time Series DBMS

Graph DBMS

Time Series 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	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.dolphindb.com

janusgraph.org

opennms.github.io/newts

Technical documentation

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

docs.janusgraph.org

github.com/OpenNMS/newts/wiki

Developer

DolphinDB, Inc

Linux Foundation; originally developed as Titan by Aurelius

OpenNMS Group

Initial release

2018

2017

2014

Current release

v2.00.4, January 2022

0.6.3, February 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache 2.0

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++

Java

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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

APIs and other access methods

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST
Java API

Supported programming languages

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

Clojure
Java
Python

Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

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