DBMS > CouchDB vs. IRONdb vs. Snowflake vs. TimesTen

System Properties Comparison CouchDB vs. IRONdb vs. Snowflake vs. TimesTen

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Cloud-based data warehousing service for structured and semi-structured data

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

couchdb.apache.org

www.circonus.com/solutions/time-series-database/

www.snowflake.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.couchdb.org/en/stable

docs.circonus.com/irondb/category/getting-started

docs.snowflake.net/manuals/index.html

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Circonus LLC.

Snowflake Computing Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2005

2017

2014

1998

Current release

3.3.3, December 2023

V0.10.20, January 2018

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

View functions in JavaScript

yes, in Lua

user defined functions

PL/SQL

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Automatic, metric affinity per node

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

yes

Multi-source replication
Source-replica replication

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 per node, eventual consistency across nodes

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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 for users can be defined per database

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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