DBMS > EJDB vs. eXtremeDB vs. Manticore Search vs. Newts vs. SQL.JS

System Properties Comparison EJDB vs. eXtremeDB vs. Manticore Search vs. Newts vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Multi-storage database for search, including full-text search.

Time Series DBMS based on Cassandra

Port of SQLite to JavaScript

Primary database model

Document store

Relational DBMS
Time Series DBMS

Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

github.com/Softmotions/ejdb

www.mcobject.com

manticoresearch.com

opennms.github.io/newts

sql.js.org

Technical documentation

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

www.mcobject.com/docs/extremedb.htm

manual.manticoresearch.com

github.com/OpenNMS/newts/wiki

sql.js.org/documentation/index.html

Developer

Softmotions

McObject

Manticore Software

OpenNMS Group

Alon Zakai

enhancements implemented by others

Initial release

2012

2001

2017

2014

2012

Current release

8.2, 2021

6.0, February 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

GPL version 2

Open Source

Apache 2.0

Open Source

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++

C++

Java

JavaScript

Server operating systems

server-less

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

support of XML interfaces available

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

in-process shared library

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

HTTP REST
Java API

JavaScript API

Supported programming languages

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

.Net
C
C#
C++
Java
Lua
Python
Scala

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Synchronous replication based on Galera library

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

except by serializing a db to a file

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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