DBMS > Cubrid vs. FoundationDB vs. Hawkular Metrics vs. Postgres-XL vs. YottaDB

System Properties Comparison Cubrid vs. FoundationDB vs. Hawkular Metrics vs. Postgres-XL vs. YottaDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

cubrid.com (korean)
cubrid.org (english)

github.com/apple/foundationdb

www.hawkular.org

www.postgres-xl.org

yottadb.com

Technical documentation

cubrid.org/manuals

apple.github.io/foundationdb

www.hawkular.org/hawkular-metrics/docs/user-guide

www.postgres-xl.org/documentation

yottadb.com/resources/documentation

Developer

CUBRID Corporation, CUBRID Foundation

FoundationDB

Community supported by Red Hat

YottaDB, LLC

Initial release

2008

2013

2014

since 2012, originally named StormDB

2001

Current release

11.0, January 2021

6.2.28, November 2020

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

AGPL 3.0

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

C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

Linux
macOS

Docker
Linux

Data scheme

yes

schema-free

some layers support schemas

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

supported in specific SQL layer only

yes

distributed, parallel query execution

by using the Octo plugin

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

HTTP REST

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

in SQL-layer only

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

Transaction concepts

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

ACID

MVCC

optimistic locking

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 and groups based on OS-security mechanisms

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