DBMS > EJDB vs. FoundationDB vs. Microsoft Azure Table Storage

System Properties Comparison EJDB vs. FoundationDB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Wide column store

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

github.com/Softmotions/ejdb

github.com/apple/foundationdb

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

apple.github.io/foundationdb

Developer

Softmotions

FoundationDB

Microsoft

Initial release

2012

2013

2012

Current release

6.2.28, November 2020

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

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

C++

Server operating systems

server-less

Linux
OS X
Windows

hosted

Data scheme

schema-free

some layers support schemas

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

SQL

Support of SQL

supported in specific SQL layer only

APIs and other access methods

in-process shared library

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

in SQL-layer only

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

in SQL-layer only

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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.

User concepts

Access control

Access rights based on private key authentication or shared access signatures

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