DBMS > AntDB vs. RDF4J vs. Spark SQL

System Properties Comparison AntDB vs. RDF4J vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

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

Primary database model

Relational DBMS

RDF store

Relational DBMS

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

Score	0.25
Rank	#303	Overall
	#137	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

rdf4j.org

spark.apache.org/sql

Technical documentation

rdf4j.org/documentation

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

Social network pages

Developer

AsiaInfo Technologies Limited

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

Apache Software Foundation

Initial release

2004

2014

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL2016 compliant

SQL-like DML and DDL statements

APIs and other access methods

JDBC
MySQL protocol compliant
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

Java
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

More information provided by the system vendor

Specific characteristics

AntDB was initiated in 2008. On the core system of operators, AntDB provides online...
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Competitive advantages

HTAP mixed load: AntDB is a universal, enterprise-level distributed relational database,...
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Typical application scenarios

As the core software of large enterprise, AntDB supports multi-scenario deployment....
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Key customers

China Mobile, China Telecom, China Unicom, Aeon Life, China Mobile Tietong, CITIC...
» more

Market metrics

More than 1 billion subscribers in 24 provinces across China are served by AntDB...
» more

Licensing and pricing models

Certificates and licenses CMMI5 Certificate licensed by CMMI Institute IT Product...
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More resources

DB-Engines blog posts

AntDB: Answer to Database Evolution - Hyperconverged All-in-One Streaming Engine
22 June 2023, Bei Mo, AntDB (sponsor)

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