DBMS > Atos Standard Common Repository vs. BigObject vs. FoundationDB vs. Google BigQuery

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. FoundationDB vs. Google BigQuery

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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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Analytic DBMS for real-time computations and queries

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

Large scale data warehouse service with append-only tables

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

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

bigobject.io

github.com/apple/foundationdb

cloud.google.com/bigquery

Technical documentation

docs.bigobject.io

apple.github.io/foundationdb

cloud.google.com/bigquery/docs

Developer

Atos Convergence Creators

BigObject, Inc.

FoundationDB

Google

Initial release

2016

2015

2013

2010

Current release

1703

6.2.28, November 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

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

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

optional

yes

some layers support typing

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

SQL-like DML and DDL statements

supported in specific SQL layer only

yes

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

in SQL-layer only

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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

none

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

in SQL-layer only

Transaction concepts

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

Atomic execution of specific operations

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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