DBMS > Drizzle vs. EJDB vs. Faircom EDGE vs. Lovefield vs. NuoDB

System Properties Comparison Drizzle vs. EJDB vs. Faircom EDGE vs. Lovefield vs. NuoDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Embeddable relational database for web apps written in pure JavaScript

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-edge

google.github.io/lovefield

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

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

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

github.com/google/lovefield/blob/master/docs/spec_index.md

doc.nuodb.com

Developer

Drizzle project, originally started by Brian Aker

Softmotions

FairCom Corporation

Google

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2008

2012

1979

2014

2013

Current release

7.2.4, September 2012

V3, October 2020

2.1.12, February 2017

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GPLv2

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

limited edition free

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++

ANSI C, C++

JavaScript

C++

Server operating systems

FreeBSD
Linux
OS X

server-less

Android
Linux

ARM, x86
Raspbian
Windows

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

tested with Chrome, Firefox, IE, Safari

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

ANSI SQL queries

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC

in-process shared library

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

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

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

JavaScript

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java, SQL

Triggers

hooks for callbacks inside the server can be used.

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

File partitioning

Customizable business rules for partitioning

none

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

when using SQL

yes

Transaction concepts

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

across SQL and NoSQL

yes

MVCC

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

Temporary table

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Standard SQL roles/ privileges, Administrative Users

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