DBMS > Drizzle vs. JaguarDB vs. Lovefield vs. Newts vs. Quasardb

System Properties Comparison Drizzle vs. JaguarDB vs. Lovefield vs. Newts vs. Quasardb

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.

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

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

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

www.jaguardb.com

google.github.io/lovefield

opennms.github.io/newts

quasar.ai

Technical documentation

www.jaguardb.com/support.html

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

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

Developer

Drizzle project, originally started by Brian Aker

DataJaguar, Inc.

Google

OpenNMS Group

quasardb

Initial release

2008

2015

2014

2009

Current release

7.2.4, September 2012

3.3 July 2023

2.1.12, February 2017

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GPL V3.0

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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

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++

the server part. Clients available in other languages

JavaScript

Java

C++

Server operating systems

FreeBSD
Linux
OS X

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

with proprietary extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

JDBC

JDBC
ODBC

HTTP REST
Java API

HTTP API

Supported programming languages

C
C++
Java
PHP

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

JavaScript

Java

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

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

none

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

yes

by using LevelDB

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

rights management via user accounts

Cryptographically strong user authentication and audit trail

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More resources

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