DBMS > Faircom DB vs. Lovefield vs. TerminusDB vs. Tkrzw

System Properties Comparison Faircom DB vs. Lovefield vs. TerminusDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

Key-value store

Secondary database models

Document store
RDF store

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.faircom.com/products/faircom-db

google.github.io/lovefield

terminusdb.com

dbmx.net/tkrzw

Technical documentation

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

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

terminusdb.github.io/terminusdb/#

Developer

FairCom Corporation

Google

DataChemist Ltd.

Mikio Hirabayashi

Initial release

1979

2014

2018

2020

Current release

V12, November 2020

2.1.12, February 2017

11.0.0, January 2023

0.9.3, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

GPL V3

Open Source

Apache Version 2.0

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

Prolog, Rust

C++

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

Linux
macOS

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

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

SQL-like query language (WOQL)

APIs and other access methods

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

JavaScript

JavaScript
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Graph Partitioning

none

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

Journaling Streams

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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 journaling

yes

In-memory capabilities

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

yes

using MemoryDB

yes

using specific database classes

User concepts

Access control

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

Role-based access control

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