DBMS > Faircom DB vs. Quasardb vs. RDF4J vs. SAP IQ vs. Snowflake

System Properties Comparison Faircom DB vs. Quasardb vs. RDF4J vs. SAP IQ vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Distributed, high-performance timeseries database

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

Columnar RDBMS optimized for Big Data analytics

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Key-value store
Relational DBMS

column-oriented

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.faircom.com/products/faircom-db

quasar.ai

rdf4j.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

doc.quasar.ai/master

rdf4j.org/documentation

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

Developer

FairCom Corporation

quasardb

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

SAP, formerly Sybase

Snowflake Computing Inc.

Initial release

1979

2009

2004

1994

2014

Current release

V12, November 2020

3.14.1, January 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

schema free, schema optional, schema required, partial schema,

schema-free

yes

RDF Schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

integer and binary

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

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

Java
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

consistent hashing

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication with selectable replication factor

none

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

by using LevelDB

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

Transient mode

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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