DBMS > Drizzle vs. Firebase Realtime Database vs. GridGain vs. Linter vs. RethinkDB

System Properties Comparison Drizzle vs. Firebase Realtime Database vs. GridGain vs. Linter vs. RethinkDB

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.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

GridGain is an in-memory computing platform, built on Apache Ignite

RDBMS for high security requirements

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

firebase.google.com/products/realtime-database

www.gridgain.com

linter.ru

rethinkdb.com

Technical documentation

firebase.google.com/docs/database

www.gridgain.com/docs/index.html

rethinkdb.com/docs

Developer

Drizzle project, originally started by Brian Aker

Google

acquired by Google 2014

GridGain Systems, Inc.

relex.ru

The Linux Foundation

since July 2017

Initial release

2008

2012

2007

1990

2009

Current release

7.2.4, September 2012

GridGain 8.5.1

2.4.1, August 2020

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, C++, .Net

C and C++

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
OS X
Solaris
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC

Android
iOS
JavaScript API
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
C++
Java
PHP

Java
JavaScript
Objective-C

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

hooks for callbacks inside the server can be used.

Callbacks are triggered when data changes

yes (cache interceptors and events)

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes (replicated cache)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

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

yes, based on authentication and database rules

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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