DBMS > DolphinDB vs. Dragonfly vs. jBASE vs. Stardog vs. TinkerGraph

System Properties Comparison DolphinDB vs. Dragonfly vs. jBASE vs. Stardog vs. TinkerGraph

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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

A robust multi-value DBMS comprising development tools and middleware

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

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

Score	2.60
Rank	#102	Overall
	#8	Time Series DBMS
	#6	Vector DBMS

Score	0.50
Rank	#245	Overall
	#35	Key-value stores

Score	1.39
Rank	#154	Overall
	#3	Multivalue DBMS

Score	1.78
Rank	#130	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.07
Rank	#346	Overall
	#35	Graph DBMS

Website

www.dolphindb.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

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

www.stardog.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

www.dragonflydb.io/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.stardog.com

Developer

DolphinDB, Inc

DragonflyDB team and community contributors

Rocket Software (formerly Zumasys)

Stardog-Union

Initial release

2018

2023

1991

2010

2009

Current release

v2.00.4, January 2022

1.0, March 2023

5.7

7.3.0, May 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

BSL 1.1

commercial

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

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

AIX
Linux
Windows

Linux
macOS
Windows

Data scheme

yes

scheme-free

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

optional

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

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

Embedded SQL for jBASE in BASIC

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

APIs and other access methods

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

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

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

TinkerPop 3

Supported programming languages

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

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
Basic
Jabbascript
Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Groovy
Java

Server-side scripts

Stored procedures

yes

Lua

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Multi-source replication in HA-Cluster

none

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

Immediate Consistency in HA-Cluster

none

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

yes

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

optional

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

Password-based authentication

Access rights can be defined down to the item level

Access rights for users and roles

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