DBMS > Drizzle vs. GigaSpaces vs. PouchDB vs. RocksDB vs. Valentina Server

System Properties Comparison Drizzle vs. GigaSpaces vs. PouchDB vs. RocksDB vs. Valentina Server

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.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Object-relational database and reports server

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Document store

Key-value store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

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

Developer

Drizzle project, originally started by Brian Aker

Gigaspaces Technologies

Apache Software Foundation

Facebook, Inc.

Paradigma Software

Initial release

2008

2000

2012

2013

1999

Current release

7.2.4, September 2012

15.5, September 2020

7.1.1, June 2019

8.11.4, April 2024

5.7.5

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

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++

Java, C++, .Net

JavaScript

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Solaris
Windows

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

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

XML can be used for describing objects metadata

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-99 for query and DML statements

yes

APIs and other access methods

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

ODBC

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java
Python
Scala

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

Triggers

hooks for callbacks inside the server can be used.

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

Role-based access control

fine grained access rights according to SQL-standard

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