DBMS > EJDB vs. Graph Engine vs. IRONdb vs. Newts

System Properties Comparison EJDB vs. Graph Engine vs. IRONdb vs. Newts

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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

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

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

Time Series DBMS based on Cassandra

Primary database model

Document store

Graph DBMS
Key-value store

Time Series DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

github.com/Softmotions/ejdb

www.graphengine.io

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

opennms.github.io/newts

Technical documentation

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

www.graphengine.io/docs/manual

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

github.com/OpenNMS/newts/wiki

Developer

Softmotions

Microsoft

Circonus LLC.

OpenNMS Group

Initial release

2012

2010

2017

2014

Current release

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

GPLv2

Open Source

MIT License

commercial

Open Source

Apache 2.0

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

.NET and C

C and C++

Java

Server operating systems

server-less

.NET

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

SQL

Support of SQL

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

APIs and other access methods

in-process shared library

RESTful HTTP API

HTTP API

HTTP REST
Java API

Supported programming languages

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

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

Java

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Automatic, metric affinity per node

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

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More resources

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