DBMS > eXtremeDB vs. Geode vs. Manticore Search vs. PouchDB vs. SQLite

System Properties Comparison eXtremeDB vs. Geode vs. Manticore Search vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

www.mcobject.com/docs/extremedb.htm

geode.apache.org/docs

manual.manticoresearch.com

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

McObject

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Manticore Software

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2001

2002

2017

2012

2000

Current release

8.2, 2021

1.1, February 2017

6.0, February 2023

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

GPL version 2

Open Source

Public Domain

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

C++

JavaScript

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM

the JDK (8 or later) is also required

FreeBSD
Linux
macOS
Windows

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

server-less

Data scheme

yes

schema-free

Fixed schema

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

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

yes

not rigid because of 'dynamic typing' concept.

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

yes

via views

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language (OQL)

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

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

Java Client API
Memcached protocol
RESTful HTTP API

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

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

View functions in JavaScript

Triggers

yes

by defining events

yes

Cache Event Listeners

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

Multi-source replication

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, on a single node

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

via file-system locks

Durability

Support for making data persistent

yes

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

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

Access rights per client and object definable

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

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