DBMS > EXASOL vs. FoundationDB vs. H2 vs. Ingres vs. Oracle Berkeley DB

System Properties Comparison EXASOL vs. FoundationDB vs. H2 vs. Ingres vs. Oracle Berkeley DB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Well established RDBMS

Widely used in-process key-value store

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

www.exasol.com

github.com/apple/foundationdb

www.h2database.com

www.actian.com/databases/ingres

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

Technical documentation

www.exasol.com/resources

apple.github.io/foundationdb

www.h2database.com/html/main.html

docs.actian.com/ingres

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

Developer

Exasol

FoundationDB

Thomas Mueller

Actian Corporation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2000

2013

2005

1974

originally developed at University Berkely in early 1970s

1994

Current release

6.2.28, November 2020

2.2.220, July 2023

11.2, May 2022

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

commercial license available

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++

Java

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

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

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.

but tools for importing/exporting data from/to XML-files available

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

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

Java
Lua
Python
R

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Java

.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

Server-side scripts

Stored procedures

user defined functions

in SQL-layer only

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

Ingres Replicator

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC

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 for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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