DBMS > Drizzle vs. PouchDB vs. TimescaleDB vs. Valentina Server vs. Yaacomo

System Properties Comparison Drizzle vs. PouchDB vs. TimescaleDB vs. Valentina Server vs. Yaacomo

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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

JavaScript DBMS with an API inspired by CouchDB

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

Object-relational database and reports server

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Relational DBMS

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

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

pouchdb.com

www.timescale.com

www.valentina-db.net

yaacomo.com

Technical documentation

pouchdb.com/guides

docs.timescale.com

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

Developer

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Timescale

Paradigma Software

Q2WEB GmbH

Initial release

2008

2012

2017

1999

2009

Current release

7.2.4, September 2012

7.1.1, June 2019

2.13.0, November 2023

5.7.5

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

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++

JavaScript

Server operating systems

FreeBSD
Linux
OS X

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

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

JDBC

HTTP REST

only for PouchDB Server
JavaScript API

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

ODBC

JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

JavaScript

.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

Server-side scripts

Stored procedures

View functions in JavaScript

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

with a proxy-based framework, named couchdb-lounge

yes, across time and space (hash partitioning) attributes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication with hot standby and reads on replicas

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

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 IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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More resources

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