DBMS > Atos Standard Common Repository vs. FoundationDB vs. Lovefield vs. SiteWhere vs. STSdb

System Properties Comparison Atos Standard Common Repository vs. FoundationDB vs. Lovefield vs. SiteWhere vs. STSdb

Editorial information provided by DB-Engines

Name

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

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Ordered key-value store. Core features are complimented by layers.

Embeddable relational database for web apps written in pure JavaScript

M2M integration platform for persisting/querying time series data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Time Series DBMS

Key-value store

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

Score	1.07
Rank	#188	Overall
	#31	Document stores
	#28	Key-value stores
	#86	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

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

github.com/apple/foundationdb

google.github.io/lovefield

github.com/sitewhere/sitewhere

github.com/STSSoft/STSdb4

Technical documentation

apple.github.io/foundationdb

github.com/google/lovefield/blob/master/docs/spec_index.md

sitewhere1.sitewhere.io/index.html

Developer

Atos Convergence Creators

FoundationDB

Google

SiteWhere

STS Soft SC

Initial release

2016

2013

2014

2010

2011

Current release

1703

6.2.28, November 2020

2.1.12, February 2017

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

Open Source

GPLv2, commercial license available

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

C++

JavaScript

Java

Server operating systems

Linux

Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

some layers support schemas

yes

predefined scheme

yes

Typing

predefined data types such as float or date

optional

some layers support typing

yes

primitive types and user defined types (classes)

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

supported in specific SQL layer only

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

LDAP

HTTP REST

.NET Client API

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

JavaScript

C#
Java

Server-side scripts

Stored procedures

in SQL-layer only

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

LDAP bind authentication

Users with fine-grained authorization concept

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