DBMS > Google Cloud Firestore vs. Postgres-XL vs. RethinkDB vs. STSdb vs. Teradata

System Properties Comparison Google Cloud Firestore vs. Postgres-XL vs. RethinkDB vs. STSdb vs. Teradata

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

firebase.google.com/products/firestore

www.postgres-xl.org

rethinkdb.com

github.com/STSSoft/STSdb4

www.teradata.com

Technical documentation

firebase.google.com/docs/firestore

www.postgres-xl.org/documentation

rethinkdb.com/docs

docs.teradata.com

Developer

Google

The Linux Foundation

since July 2017

STS Soft SC

Teradata

Initial release

2017

2014

since 2012, originally named StormDB

2009

2011

1984

Current release

10 R1, October 2018

2.4.1, August 2020

4.0.8, September 2015

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache Version 2

Open Source

GPLv2, commercial license available

commercial

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

Linux
macOS

Linux
OS X
Windows

Windows

hosted
Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

primitive types and user defined types (classes)

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

distributed, parallel query execution

yes

SQL 2016 + extensions

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

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

C#
Java

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes, with Cloud Functions

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

range based

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

MVCC

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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.

fine grained access rights according to SQL-standard

yes

users and table-level permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

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