DBMS > Apache Doris vs. Google Cloud Firestore vs. SpaceTime vs. TDSQL for MySQL

System Properties Comparison Apache Doris vs. Google Cloud Firestore vs. SpaceTime vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

firebase.google.com/products/firestore

www.mireo.com/spacetime

www.tencentcloud.com/products/dcdb

Technical documentation

github.com/apache/doris/wiki

firebase.google.com/docs/firestore

www.tencentcloud.com/document/product/1042

Developer

Apache Software Foundation, originally contributed from Baidu

Google

Mireo

Tencent

Initial release

2017

2020

2013

Current release

1.2.2, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux

hosted

Linux

hosted

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.

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

yes

APIs and other access methods

JDBC
MySQL client

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

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

C#
C++
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Fixed-grid hypercubes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Real-time block device replication (DRBD)

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

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

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24 June 2022, InfoWorld

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20 June 2022, Datanami

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