DBMS > EXASOL vs. Graph Engine vs. gStore vs. IRONdb

System Properties Comparison EXASOL vs. Graph Engine vs. gStore vs. IRONdb

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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 in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A native Graph DBMS to store and maintain very large RDF datasets.

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Graph DBMS
RDF store

Time Series DBMS

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

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Website

www.exasol.com

www.graphengine.io

en.gstore.cn

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

Technical documentation

www.exasol.com/resources

www.graphengine.io/docs/manual

en.gstore.cn/#/enDocs

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

Developer

Exasol

Microsoft

Circonus LLC.

Initial release

2000

2010

2016

2017

Current release

1.2, November 2023

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

BSD

commercial

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

.NET and C

C++

C and C++

Server operating systems

.NET

Linux

Data scheme

yes

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

yes

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

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

HTTP API
SPARQL 1.1

HTTP API

Supported programming languages

Java
Lua
Python
R

C#
C++
F#
Visual Basic

C++
Java
JavaScript (Node.js)
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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