DBMS > Geode vs. IBM Cloudant vs. RethinkDB vs. TimescaleDB

System Properties Comparison Geode vs. IBM Cloudant vs. RethinkDB vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Key-value store

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

geode.apache.org

www.ibm.com/products/cloudant

rethinkdb.com

www.timescale.com

Technical documentation

geode.apache.org/docs

cloud.ibm.com/docs/Cloudant

rethinkdb.com/docs

docs.timescale.com

Developer

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

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

The Linux Foundation

since July 2017

Timescale

Initial release

2002

2010

2009

2017

Current release

1.1, February 2017

2.4.1, August 2020

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

View functions (Map-Reduce) in JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Cache Event Listeners

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

atomic operations within a document possible

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

MVCC based

yes

Durability

Support for making data persistent

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

Access rights for users can be defined per database

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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More resources

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