DBMS > Dgraph vs. EsgynDB vs. PostgreSQL vs. Quasardb vs. Tkrzw

System Properties Comparison Dgraph vs. EsgynDB vs. PostgreSQL vs. Quasardb vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Widely used open source RDBMS

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

Distributed, high-performance timeseries database

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Graph DBMS

Relational DBMS

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

Time Series DBMS

Key-value store

Secondary database models

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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

Technical documentation

dgraph.io/docs

www.postgresql.org/docs

doc.quasar.ai/master

Developer

Dgraph Labs, Inc.

Esgyn

PostgreSQL Global Development Group

www.postgresql.org/developer

quasardb

Mikio Hirabayashi

Initial release

2016

2015

1989

1989: Postgres, 1996: PostgreSQL

2009

2020

Current release

16.3, May 2024

3.14.1, January 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux

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

BSD
Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like query language

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

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

HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

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

yes

Sharding

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

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

using specific database classes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

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