DBMS > Google Cloud Firestore vs. PlanetScale vs. Snowflake vs. STSdb vs. TerarkDB

System Properties Comparison Google Cloud Firestore vs. PlanetScale vs. Snowflake vs. STSdb vs. TerarkDB

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.

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store

Relational DBMS

Key-value store

Secondary database models

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	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

firebase.google.com/products/firestore

planetscale.com

www.snowflake.com

github.com/STSSoft/STSdb4

github.com/bytedance/terarkdb

Technical documentation

firebase.google.com/docs/firestore

planetscale.com/docs

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Google

PlanetScale

Snowflake Computing Inc.

STS Soft SC

ByteDance, originally Terark

Initial release

2017

2020

2014

2011

2016

Current release

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

commercial

restricted open source version 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.

Implementation language

C++

Server operating systems

hosted

Docker
Linux
macOS

hosted

Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

yes

APIs and other access methods

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

ADO.NET
JDBC
MySQL protocol
ODBC

CLI Client
JDBC
ODBC

.NET Client API

C++ API
Java API

Supported programming languages

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

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

JavaScript (Node.js)
Python

C#
Java

C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

user defined functions

Triggers

yes, with Cloud Functions

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

yes

none

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

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

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.

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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