DBMS > EJDB vs. EXASOL vs. IRONdb vs. SiteWhere

System Properties Comparison EJDB vs. EXASOL vs. IRONdb vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

M2M integration platform for persisting/querying time series data

Primary database model

Document store

Relational DBMS

Time Series DBMS

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

Score	0.09
Rank	#317	Overall
	#42	Document stores

Score	2.97
Rank	#103	Overall
	#53	Relational DBMS

Score	0.00
Rank	#363	Overall
	#34	Time Series DBMS

Score	0.00
Rank	#363	Overall
	#34	Time Series DBMS

Website

ejdb.org

www.exasol.com

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

sitewhere.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.exasol.com/resources

docs.circonus.com/irondb

sitewhere.io/docs/2.1.0

Developer

Softmotions

Exasol

Circonus LLC.

SiteWhere

Initial release

2012

2000

2017

2010

Current release

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Common Public Attribution License Version 1.0

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

C and C++

Java

Server operating systems

server-less

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes

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

APIs and other access methods

in-process shared library

.Net
JDBC
ODBC
WebSocket

HTTP API

HTTP REST

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic, metric affinity per node

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

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 with fine-grained authorization concept

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