DBMS > Ingres vs. RDF4J vs. SAP HANA vs. Sequoiadb

System Properties Comparison Ingres vs. RDF4J vs. SAP HANA vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

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

In-memory, column based data store. Available as appliance or cloud service

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

RDF store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

www.actian.com/databases/ingres

rdf4j.org

www.sap.com/products/hana.html

www.sequoiadb.com

Technical documentation

docs.actian.com/ingres

rdf4j.org/documentation

help.sap.com/hana

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Actian Corporation

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

SAP

Sequoiadb Ltd.

Initial release

1974

originally developed at University Berkely in early 1970s

2004

2010

2013

Current release

12.0, July 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Appliance or cloud-service

Linux

Data scheme

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

none

yes

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

Eventual 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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

fine grained access rights according to SQL-standard

yes

simple password-based access control

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