DBMS > Amazon Redshift vs. FoundationDB vs. HugeGraph vs. InterSystems Caché vs. MonetDB

System Properties Comparison Amazon Redshift vs. FoundationDB vs. HugeGraph vs. InterSystems Caché vs. MonetDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

A fast-speed and highly-scalable Graph DBMS

A multi-model DBMS and application server

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Graph DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Website

aws.amazon.com/redshift

github.com/apple/foundationdb

github.com/hugegraph
hugegraph.apache.org

www.intersystems.com/products/cache

www.monetdb.org

Technical documentation

docs.aws.amazon.com/redshift

apple.github.io/foundationdb

hugegraph.apache.org/docs

docs.intersystems.com

www.monetdb.org/Documentation

Developer

Amazon (based on PostgreSQL)

FoundationDB

Baidu

InterSystems

MonetDB BV

Initial release

2012

2013

2018

1997

2004

Current release

6.2.28, November 2020

0.9

2018.1.4, May 2020

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla Public License 2.0

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

C++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Unix

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

depending on used data model

yes

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

Secondary indexes

restricted

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

supported in specific SQL layer only

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Groovy
Java
Python

C#
C++
Java

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

in SQL-layer only

asynchronous Gremlin script jobs

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

yes

edges in graph

yes

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

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

Users, roles and permissions

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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