DBMS > Dgraph vs. Fujitsu Enterprise Postgres vs. LokiJS vs. Oracle Berkeley DB vs. Oracle Coherence

System Properties Comparison Dgraph vs. Fujitsu Enterprise Postgres vs. LokiJS vs. Oracle Berkeley DB vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

In-memory JavaScript DBMS

Widely used in-process key-value store

Oracles in-memory data grid solution

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

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

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

dgraph.io

www.postgresql.fastware.com

github.com/techfort/LokiJS

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

www.oracle.com/java/coherence

Technical documentation

dgraph.io/docs

www.postgresql.fastware.com/product-manuals

techfort.github.io/LokiJS

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

docs.oracle.com/en/middleware/standalone/coherence

Developer

Dgraph Labs, Inc.

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

Initial release

2016

2014

1994

2007

Current release

Fujitsu Enterprise Postgres 14, January 2022

18.1.40, May 2020

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial license available

commercial

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

JavaScript

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

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

All OS with a Java VM

Data scheme

schema-free

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

via views

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

JavaScript API

JCache
JPA
RESTful HTTP API

Supported programming languages

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

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

JavaScript

.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
C++
Java

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

Triggers

yes

only for the SQL API

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

yes

partitioning by range, list and by hash

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication

none

Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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