DBMS > Geode vs. PouchDB vs. Riak KV vs. SQLite vs. Trafodion

System Properties Comparison Geode vs. PouchDB vs. Riak KV vs. SQLite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

JavaScript DBMS with an API inspired by CouchDB

Distributed, fault tolerant key-value store

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

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

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

geode.apache.org/docs

pouchdb.com/guides

www.tiot.jp/riak-docs/riak/kv/latest

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

Developer

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

Apache Software Foundation

OpenSource, formerly Basho Technologies

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Initial release

2002

2012

2009

2000

2014

Current release

1.1, February 2017

7.1.1, June 2019

3.2.0, December 2022

3.45.3 (15 April 2024), April 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache version 2, commercial enterprise edition

Open Source

Public Domain

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

Java

JavaScript

Erlang

C++, Java

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

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

Linux
OS X

server-less

Linux

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

restricted

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

SQL-92 is not fully supported

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

Supported programming languages

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

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

Erlang

Java Stored Procedures

Triggers

yes

Cache Event Listeners

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

selectable replication factor

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

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

yes, using Riak Security

fine grained access rights according to SQL-standard

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