DBMS > DataFS vs. DolphinDB vs. Greenplum vs. Newts vs. Stardog

System Properties Comparison DataFS vs. DolphinDB vs. Greenplum vs. Newts vs. Stardog

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Time Series DBMS based on Cassandra

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Graph DBMS

Relational DBMS

Document store
Spatial DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

newdatabase.com

www.dolphindb.com

greenplum.org

opennms.github.io/newts

www.stardog.com

Technical documentation

dev.mobiland.com/Overview.xsp

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

docs.greenplum.org

github.com/OpenNMS/newts/wiki

docs.stardog.com

Developer

Mobiland AG

DolphinDB, Inc

Pivotal Software Inc.

OpenNMS Group

Stardog-Union

Initial release

2018

2005

2014

2010

Current release

1.1.263, October 2022

v2.00.4, January 2022

7.0.0, September 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Windows

Linux
Windows

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

schema-free and OWL/RDFS-schema support

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

since Version 4.2

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

JDBC
ODBC

HTTP REST
Java API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
C
C#
C++
VB.Net

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

C
Java
Perl
Python
R

Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

no, except callback-events from server when changes happened

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

horizontal partitioning

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on Cassandra

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

yes

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

User concepts

Access control

Windows-Profile

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Access rights for users and roles

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