DBMS > Google Cloud Firestore vs. TimesTen vs. YTsaurus

System Properties Comparison Google Cloud Firestore vs. TimesTen vs. YTsaurus

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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.

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store

Relational DBMS

Document store
Key-value store

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.15
Rank	#323	Overall
	#44	Document stores
	#47	Key-value stores

Website

firebase.google.com/products/firestore

www.oracle.com/database/technologies/related/timesten.html

ytsaurus.tech

Technical documentation

firebase.google.com/docs/firestore

docs.oracle.com/en/database/other-databases/timesten/index.html

ytsaurus.tech/docs/en

Developer

Google

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Yandex

Initial release

2017

1998

2023

Current release

Release 22.1

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

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

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Ubuntu

Data scheme

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

YQL, an SQL-based language, is supported

APIs and other access methods

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

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

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

C
C++
Java
Node.js
PL/SQL
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

PL/SQL

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

yes

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

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

by means of logfiles and checkpoints

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

Access Control Lists

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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