DBMS > Lovefield vs. OrigoDB vs. Quasardb vs. Tkrzw

System Properties Comparison Lovefield vs. OrigoDB vs. Quasardb vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

A fully ACID in-memory object graph database

Distributed, high-performance timeseries database

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

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Key-value store

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

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

Website

google.github.io/lovefield

origodb.com

quasar.ai

dbmx.net/tkrzw

Technical documentation

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

origodb.com/docs

doc.quasar.ai/master

Developer

Google

Robert Friberg et al

quasardb

Mikio Hirabayashi

Initial release

2014

2009

under the name LiveDB

2009

2020

Current release

2.1.12, February 2017

3.14.1, January 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

JavaScript

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux
Windows

BSD
Linux
OS X
Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

integer and binary

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.

can be achieved using .NET

Secondary indexes

yes

with tags

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

.NET Client API
HTTP API
LINQ

HTTP API

Supported programming languages

JavaScript

.Net

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

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

Write ahead log

yes

by using LevelDB

yes

In-memory capabilities

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

yes

using MemoryDB

yes

Transient mode

yes

using specific database classes

User concepts

Access control

Role based authorization

Cryptographically strong user authentication and audit trail

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