DBMS > EXASOL vs. IRONdb vs. Microsoft SQL Server vs. RDF4J vs. YDB

System Properties Comparison EXASOL vs. IRONdb vs. Microsoft SQL Server vs. RDF4J vs. YDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Microsofts flagship relational DBMS

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

www.exasol.com

www.circonus.com/solutions/time-series-database/

www.microsoft.com/en-us/sql-server

rdf4j.org

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

www.exasol.com/resources

docs.circonus.com/irondb/category/getting-started

learn.microsoft.com/en-US/sql/sql-server

rdf4j.org/documentation

ydb.tech/en/docs

Developer

Exasol

Circonus LLC.

Microsoft

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

Yandex

Initial release

2000

2017

1989

2004

2019

Current release

V0.10.20, January 2018

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

Java

Server operating systems

Linux

Linux
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

RDF Schemas

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL-like query language (YQL)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Java
Lua
Python
R

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes, but depending on the SQL-Server Edition

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

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

ACID

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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