DBMS > Atos Standard Common Repository vs. Badger vs. FatDB vs. Geode vs. KairosDB

System Properties Comparison Atos Standard Common Repository vs. Badger vs. FatDB vs. Geode vs. KairosDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Document store
Key-value store

Key-value store

Document store
Key-value store

Key-value store

Time Series DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

github.com/dgraph-io/badger

geode.apache.org

github.com/kairosdb/kairosdb

Technical documentation

godoc.org/github.com/dgraph-io/badger

geode.apache.org/docs

kairosdb.github.io

Developer

Atos Convergence Creators

DGraph Labs

FatCloud

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

Initial release

2016

2017

2012

2002

2013

Current release

1703

1.1, February 2017

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language (OQL)

APIs and other access methods

LDAP

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

Java Client API
Memcached protocol
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

All languages with LDAP bindings

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

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions

Triggers

yes

via applications

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

Multi-source replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

yes, on a single node

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

User concepts

Access control

LDAP bind authentication

Can implement custom security layer via applications

Access rights per client and object definable

simple password-based access control

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