DBMS > DolphinDB vs. GigaSpaces vs. OpenQM vs. RDF4J vs. TimescaleDB

System Properties Comparison DolphinDB vs. GigaSpaces vs. OpenQM vs. RDF4J vs. TimescaleDB

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.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Time Series DBMS
Vector DBMS

Document store
Object oriented DBMS

Values are user defined objects

Multivalue DBMS

RDF store

Time Series DBMS

Secondary database models

Relational DBMS

Graph DBMS
Search engine

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

www.dolphindb.com

www.gigaspaces.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

rdf4j.org

www.timescale.com

Technical documentation

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

docs.gigaspaces.com/latest/landing.html

rdf4j.org/documentation

docs.timescale.com

Developer

DolphinDB, Inc

Gigaspaces Technologies

Rocket Software, originally Martin Phillips

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

Timescale

Initial release

2018

2000

1993

2004

2017

Current release

v2.00.4, January 2022

15.5, September 2020

3.4-12

2.15.0, May 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPLv2, extended commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

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, C++, .Net

Java

Server operating systems

Linux
Windows

Linux
macOS
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

with some exceptions

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-99 for query and DML statements

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C++
Java
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

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

in-memory storage is supported as well

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

Role-based access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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