DBMS > AgensGraph vs. FoundationDB vs. Graph Engine vs. Oracle Berkeley DB vs. Yanza

System Properties Comparison AgensGraph vs. FoundationDB vs. Graph Engine vs. Oracle Berkeley DB vs. Yanza

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Widely used in-process key-value store

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS
Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Graph DBMS
Key-value store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

bitnine.net/agensgraph

github.com/apple/foundationdb

www.graphengine.io

www.oracle.com/database/technologies/related/berkeleydb.html

yanza.com

Technical documentation

bitnine.net/documentation

apple.github.io/foundationdb

www.graphengine.io/docs/manual

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Bitnine Global Inc.

FoundationDB

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Yanza

Initial release

2016

2013

2010

1994

2015

Current release

2.1, December 2018

6.2.28, November 2020

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

MIT License

Open Source

commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

.NET and C

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X
Windows

.NET

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Windows

Data scheme

depending on used data model

schema-free

some layers support schemas

yes

schema-free

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

supported in specific SQL layer only

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

HTTP API

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C#
C++
F#
Visual Basic

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

in SQL-layer only

yes

Triggers

yes

only for the SQL API

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

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