DBMS > AgensGraph vs. DolphinDB vs. Graph Engine vs. PostgreSQL vs. ToroDB

System Properties Comparison AgensGraph vs. DolphinDB vs. Graph Engine vs. PostgreSQL vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS
Relational DBMS

Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store

Secondary database models

Relational DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

bitnine.net/agensgraph

www.dolphindb.com

www.graphengine.io

www.postgresql.org

github.com/torodb/server

Technical documentation

bitnine.net/documentation

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

www.graphengine.io/docs/manual

www.postgresql.org/docs

Developer

Bitnine Global Inc.

DolphinDB, Inc

Microsoft

PostgreSQL Global Development Group

www.postgresql.org/developer

8Kdata

Initial release

2016

2018

2010

1989

1989: Postgres, 1996: PostgreSQL

2016

Current release

2.1, December 2018

v2.00.4, January 2022

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free community version available

Open Source

MIT License

Open Source

BSD

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

C++

.NET and C

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

.NET

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

All OS with a Java 7 VM

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

Cypher Query Language
JDBC

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

RESTful HTTP API

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

Supported programming languages

C
Java
JavaScript
Python

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

C#
C++
F#
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

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

Foreign keys

Referential integrity

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

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