DBMS > Faircom DB vs. Lovefield vs. Netezza vs. ToroDB

System Properties Comparison Faircom DB vs. Lovefield vs. Netezza vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Embeddable relational database for web apps written in pure JavaScript

Data warehouse and analytics appliance part of IBM PureSystems

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

www.faircom.com/products/faircom-db

google.github.io/lovefield

www.ibm.com/products/netezza

github.com/torodb/server

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

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

Developer

FairCom Corporation

Google

IBM

8Kdata

Initial release

1979

2014

2000

2016

Current release

V13, July 2024

2.1.12, February 2017

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Open Source

AGPL-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

ANSI C, C++

JavaScript

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

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

tested with Chrome, Firefox, IE, Safari

Linux

included in appliance

All OS with a Java 7 VM

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

JavaScript

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Users with fine-grained authorization concept

Access rights for users and roles

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More resources

Recent citations in the news

FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple'
4 June 2024, Business Wire

provided by Google News

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21 August 2019, AWS Blog

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1 August 2023, The Register

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provided by Google News

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