DBMS > Apache Doris vs. DuckDB vs. Fujitsu Enterprise Postgres vs. Stardog

System Properties Comparison Apache Doris vs. DuckDB vs. Fujitsu Enterprise Postgres vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Primary database model

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

doris.apache.org
github.com/apache/doris

duckdb.org

www.postgresql.fastware.com

www.stardog.com

Technical documentation

github.com/apache/doris/wiki

duckdb.org/docs

www.postgresql.fastware.com/product-manuals

docs.stardog.com

Developer

Apache Software Foundation, originally contributed from Baidu

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Stardog-Union

Initial release

2017

2018

2010

Current release

1.2.2, February 2023

0.10, February 2024

Fujitsu Enterprise Postgres 14, January 2022

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

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

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

Linux

server-less

Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

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

APIs and other access methods

JDBC
MySQL client

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

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

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

Supported programming languages

Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

partitioning by range, list and by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

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More resources

Recent citations in the news

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5 March 2024, Datanami

DuckDB and AWS — How to Aggregate 100 Million Rows in 1 Minute
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MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
20 September 2023, PR Newswire

provided by Google News

Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

Supporting Business Continuity with Postgres on IBM Cloud LinuxONE Virtual Servers for VPC
24 September 2021, ibm.com

provided by Google News

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