DBMS > Drizzle vs. Quasardb vs. TimescaleDB vs. Valentina Server vs. WakandaDB

System Properties Comparison Drizzle vs. Quasardb vs. TimescaleDB vs. Valentina Server vs. WakandaDB

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.

Distributed, high-performance timeseries database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Object-relational database and reports server

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Relational DBMS

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

doc.quasar.ai/master

docs.timescale.com

valentina-db.com/docs/dokuwiki/v5/doku.php

wakanda.github.io/doc

Developer

Drizzle project, originally started by Brian Aker

quasardb

Timescale

Paradigma Software

Wakanda SAS

Initial release

2008

2009

2017

1999

2012

Current release

7.2.4, September 2012

3.14.1, January 2024

2.15.0, May 2024

5.7.5

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GNU GPL

commercial

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

Open Source

Apache 2.0

commercial

Open Source

AGPLv3, extended commercial license available

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++

C++, JavaScript

Server operating systems

FreeBSD
Linux
OS X

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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

with tags

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

JDBC

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ODBC

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

JavaScript

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

Source-replica replication with hot standby and reads on replicas

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

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 LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

yes

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More resources

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