DBMS > H2 vs. JanusGraph vs. Oracle Berkeley DB vs. Typesense

System Properties Comparison H2 vs. JanusGraph vs. Oracle Berkeley DB vs. Typesense

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Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used in-process key-value store

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Relational DBMS

Graph DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Search engine

Secondary database models

Spatial DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.76
Rank	#219	Overall
	#14	Search engines

Website

www.h2database.com

janusgraph.org

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

typesense.org

Technical documentation

www.h2database.com/html/main.html

docs.janusgraph.org

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

typesense.org/docs

Developer

Thomas Mueller

Linux Foundation; originally developed as Titan by Aurelius

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2005

2017

1994

2015

Current release

2.2.220, July 2023

0.6.3, February 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

GPL V3

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

Java

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

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Unix
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

yes

schema-free

pre-defined schema optional

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

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Supported programming languages

Java

Clojure
Java
Python

.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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

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

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

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