DBMS > Google Cloud Firestore vs. GreptimeDB vs. Kinetica vs. Kingbase vs. MariaDB

System Properties Comparison Google Cloud Firestore vs. GreptimeDB vs. Kinetica vs. Kingbase vs. MariaDB

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.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Fully vectorized database across both GPUs and CPUs

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Website

firebase.google.com/products/firestore

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

Technical documentation

firebase.google.com/docs/firestore

docs.greptime.com

docs.kinetica.com

mariadb.com/kb/en/library

Developer

Google

Greptime Inc.

Kinetica

BeiJing KINGBASE Information technologies inc.

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Initial release

2017

2022

2012

1999

2009

Fork of MySQL, which was first released in 1995

Current release

7.1, August 2021

V8.0, August 2021

11.3.2, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2, commercial enterprise subscription available

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.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

Implementation language

Rust

C, C++

C and Java

C and C++

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

Linux
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

Dynamic columns are supported

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

yes

SQL-like DML and DDL statements

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

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

gRPC
HTTP API
JDBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

C++
Erlang
Go
Java
JavaScript

C++
Java
JavaScript (Node.js)
Python

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

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

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Python

user defined functions

yes

PL/SQL compatibility added with version 10.3

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

horizontal partitioning (by range, list and hash) and vertical partitioning

several options for horizontal partitioning and Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

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

Durability

Support for making data persistent

yes

not for in-memory storage engine

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

with MEMORY storage engine

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.

Simple rights management via user accounts

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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