DBMS > EJDB vs. Fauna vs. GridGain vs. Oracle Berkeley DB vs. VoltDB

System Properties Comparison EJDB vs. Fauna vs. GridGain vs. Oracle Berkeley DB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

GridGain is an in-memory computing platform, built on Apache Ignite

Widely used in-process key-value store

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Document store
Graph DBMS
Relational DBMS
Time Series 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

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

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

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/Softmotions/ejdb

fauna.com

www.gridgain.com

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

www.voltdb.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.fauna.com

www.gridgain.com/docs/index.html

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

docs.voltdb.com

Developer

Softmotions

Fauna, Inc.

GridGain Systems, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

VoltDB Inc.

Initial release

2012

2014

2007

1994

2010

Current release

GridGain 8.5.1

18.1.40, May 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Java, C++, .Net

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

Java, C++

Server operating systems

server-less

hosted

Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

ANSI-99 for query and DML statements, subset of DDL

yes

SQL interfaced based on SQLite is available

yes

only a subset of SQL 99

APIs and other access methods

in-process shared library

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C#
C++
Java
PHP
Python
Ruby
Scala

.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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

Java

Triggers

yes (cache interceptors and events)

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes (replicated cache)

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

Security Hooks for custom implementations

Users and roles with access to stored procedures

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