DBMS > FatDB vs. IRONdb vs. Riak TS vs. Sadas Engine vs. Yaacomo

System Properties Comparison FatDB vs. IRONdb vs. Riak TS vs. Sadas Engine vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.25
Rank	#308	Overall
	#26	Time Series DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

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

www.sadasengine.com

yaacomo.com

Technical documentation

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

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

FatCloud

Circonus LLC.

Open Source, formerly Basho Technologies

SADAS s.r.l.

Q2WEB GmbH

Initial release

2012

2017

2015

2006

2009

Current release

V0.10.20, January 2018

3.0.0, September 2022

8.0

License

Commercial or Open Source

commercial

Open Source

commercial

free trial version available

commercial

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++

Erlang

C++

Server operating systems

Windows

Linux

Linux
OS X

AIX
Linux
Windows

Android
Linux
Windows

Data scheme

schema-free

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

Via inetgration in SQL Server

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

yes, limited

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Supported programming languages

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

yes, in Lua

Erlang

Triggers

yes

via applications

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

configurable replication factor, datacenter aware

selectable replication factor

none

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

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Can implement custom security layer via applications

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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