DBMS > FoundationDB vs. GBase vs. IRONdb vs. JanusGraph vs. mSQL

System Properties Comparison FoundationDB vs. GBase vs. IRONdb vs. JanusGraph vs. mSQL

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

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

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

github.com/apple/foundationdb

www.gbase.cn

www.circonus.com/solutions/time-series-database/

janusgraph.org

hughestech.com.au/products/msql

Technical documentation

apple.github.io/foundationdb

docs.circonus.com/irondb/category/getting-started

docs.janusgraph.org

Developer

FoundationDB

General Data Technology Co., Ltd.

Circonus LLC.

Linux Foundation; originally developed as Titan by Aurelius

Hughes Technologies

Initial release

2013

2004

2017

1994

Current release

6.2.28, November 2020

GBase 8a, GBase 8s, GBase 8c

V0.10.20, January 2018

0.6.3, February 2023

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

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

C++

C, Java, Python

C and C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

some layers support schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

some layers support typing

yes

text, numeric, histograms

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

supported in specific SQL layer only

Standard with numerous extensions

SQL-like query language (Circonus Analytics Query Language: CAQL)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Clojure
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

in SQL-layer only

user defined functions

yes, in Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Automatic, metric affinity per node

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

in SQL-layer only

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

User concepts

Access control

yes

User authentification and security via Rexster Graph Server

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