DBMS > Dgraph vs. PostgreSQL vs. StarRocks

System Properties Comparison Dgraph vs. PostgreSQL vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Widely used open source RDBMS

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

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.

Relational DBMS

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	1.25
Rank	#163	Overall
	#15	Graph DBMS

Score	663.41
Rank	#4	Overall
	#4	Relational DBMS

Score	1.13
Rank	#170	Overall
	#78	Relational DBMS

Website

dgraph.io

www.postgresql.org

www.starrocks.io

Technical documentation

dgraph.io/docs

www.postgresql.org/docs

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Dgraph Labs, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

The Linux Foundation

since Feb 2023

Initial release

2016

1989

1989: Postgres, 1996: PostgreSQL

2020

Current release

16.4, August 2024

3.3, June 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Server operating systems

Linux
OS X
Windows

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

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

APIs and other access methods

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

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

JDBC
MySQL protocol

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

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

In-memory capabilities

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

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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