DBMS > Dgraph vs. PostgreSQL vs. RDF4J vs. Spark SQL vs. TimesTen

System Properties Comparison Dgraph vs. PostgreSQL vs. RDF4J vs. Spark SQL vs. TimesTen

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

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

In-Memory RDBMS compatible to Oracle

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.

RDF store

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	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

dgraph.io/docs

www.postgresql.org/docs

rdf4j.org/documentation

spark.apache.org/docs/latest/sql-programming-guide.html

docs.oracle.com/database/timesten-18.1

Developer

Dgraph Labs, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

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

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

1989

1989: Postgres, 1996: PostgreSQL

2004

2014

1998

Current release

16.3, May 2024

3.5.0 ( 2.13), September 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

Linux
OS X
Windows

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

Linux
OS X
Unix
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

RDF Schemas

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

SQL-like DML and DDL statements

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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
PHP
Python

Java
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

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

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

yes, utilizing Spark Core

none

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

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

More information provided by the system vendor

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