DBMS > Graph Engine vs. HyperSQL vs. Oracle Berkeley DB

System Properties Comparison Graph Engine vs. HyperSQL vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used in-process key-value store

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

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

Website

www.graphengine.io

hsqldb.org

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

Technical documentation

www.graphengine.io/docs/manual

hsqldb.org/web/hsqlDocsFrame.html

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

Developer

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2010

2001

1994

Current release

2.7.2, June 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT License

Open Source

based on BSD license

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

.NET and C

Java

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

Server operating systems

.NET

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC
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

yes

Java, SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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More resources

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Trinity
2 June 2023, Microsoft

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