DBMS > eXtremeDB vs. Manticore Search vs. NSDb vs. PouchDB vs. STSdb

System Properties Comparison eXtremeDB vs. Manticore Search vs. NSDb vs. PouchDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

JavaScript DBMS with an API inspired by CouchDB

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS
Time Series 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	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

www.mcobject.com/docs/extremedb.htm

manual.manticoresearch.com

nsdb.io/Architecture

pouchdb.com/guides

Developer

McObject

Manticore Software

Apache Software Foundation

STS Soft SC

Initial release

2001

2017

2012

2011

Current release

8.2, 2021

6.0, February 2023

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

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, Scala

JavaScript

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux
macOS

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

Windows

Data scheme

yes

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes: int, bigint, decimal, string

yes

primitive types and user defined types (classes)

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

all fields are automatically indexed

yes

via views

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

APIs and other access methods

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

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

gRPC
HTTP REST
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

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

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

Java
Scala

JavaScript

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions

View functions in JavaScript

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

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

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

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.

Using Apache Lucene

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

More information provided by the system vendor

Specific characteristics

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

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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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...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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