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

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

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Document store

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.exasol.com

www.graphengine.io

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.exasol.com/resources

www.graphengine.io/docs/manual

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

www.xtdb.com/docs

Developer

Exasol

Microsoft

Circonus LLC.

Juxt Ltd.

Initial release

2000

2010

2017

2019

Current release

V0.10.20, January 2018

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Open Source

MIT License

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 and C++

Clojure

Server operating systems

.NET

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes, extensible-data-notation format

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)

limited SQL, making use of Apache Calcite

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

HTTP API

HTTP REST
JDBC

Supported programming languages

Java
Lua
Python
R

C#
C++
F#
Visual Basic

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

Clojure
Java

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes, each node contains all data

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

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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