DBMS > DolphinDB vs. RDF4J vs. RisingWave vs. SwayDB

System Properties Comparison DolphinDB vs. RDF4J vs. RisingWave vs. SwayDB

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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.

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

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.dolphindb.com

rdf4j.org

www.risingwave.com/database

swaydb.simer.au

Technical documentation

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

rdf4j.org/documentation

docs.risingwave.com/docs/current/intro

Developer

DolphinDB, Inc

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

RisingWave Labs

Simer Plaha

Initial release

2018

2004

2022

2018

Current release

v2.00.4, January 2022

1.2, September 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

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

Rust

Scala

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

yes

APIs and other access methods

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
PostgreSQL wire protocol

Supported programming languages

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

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Isolation support depends on the API used

Atomic execution of operations

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

Users and Roles

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