DBMS > FoundationDB vs. Geode vs. Hawkular Metrics vs. Microsoft SQL Server vs. Postgres-XL

System Properties Comparison FoundationDB vs. Geode vs. Hawkular Metrics vs. Microsoft SQL Server vs. Postgres-XL

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Microsofts flagship relational DBMS

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

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

github.com/apple/foundationdb

geode.apache.org

www.hawkular.org

www.microsoft.com/en-us/sql-server

www.postgres-xl.org

Technical documentation

apple.github.io/foundationdb

geode.apache.org/docs

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

learn.microsoft.com/en-US/sql/sql-server

www.postgres-xl.org/documentation

Developer

FoundationDB

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Community supported by Red Hat

Microsoft

Initial release

2013

2002

2014

1989

2014

since 2012, originally named StormDB

Current release

6.2.28, November 2020

1.1, February 2017

SQL Server 2022, November 2022

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

Linux
Windows

Linux
macOS

Data scheme

schema-free

some layers support schemas

schema-free

yes

Typing

predefined data types such as float or date

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

supported in specific SQL layer only

SQL-like query language (OQL)

yes

distributed, parallel query execution

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
All JVM based languages
C++
Groovy
Java
Scala

Go
Java
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

in SQL-layer only

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

MVCC

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

Access rights per client and object definable

fine grained access rights according to SQL-standard

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