DBMS > Google Cloud Firestore vs. Kinetica vs. Memcached vs. MySQL

System Properties Comparison Google Cloud Firestore vs. Kinetica vs. Memcached vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Fully vectorized database across both GPUs and CPUs

In-memory key-value store, originally intended for caching

Widely used open source RDBMS

Primary database model

Key/Value like access via memcached API

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

firebase.google.com/products/firestore

www.kinetica.com

www.memcached.org

www.mysql.com

Technical documentation

firebase.google.com/docs/firestore

docs.kinetica.com

github.com/memcached/memcached/wiki

dev.mysql.com/doc

Developer

Google

Kinetica

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2017

2012

2003

1995

Current release

7.1, August 2021

1.6.25, March 2024

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++

C and C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

yes

proprietary syntax

Triggers

yes, with Cloud Functions

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users and roles on table level

yes

using SASL (Simple Authentication and Security Layer) protocol

Users with fine-grained authorization concept

no user groups or roles

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