DBMS > Google Cloud Firestore vs. TimescaleDB vs. TimesTen vs. Trino

System Properties Comparison Google Cloud Firestore vs. TimescaleDB vs. TimesTen vs. Trino

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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.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

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.

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

firebase.google.com/products/firestore

www.timescale.com

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

trino.io

Technical documentation

firebase.google.com/docs/firestore

docs.timescale.com

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

trino.io/broadcast
trino.io/docs/current

Developer

Google

Timescale

Oracle

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

Trino Software Foundation

Initial release

2017

1998

2012

2020 rebranded from PrestoSQL

Current release

2.15.0, May 2024

Release 22.1

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 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

Java

Server operating systems

hosted

Linux
OS X
Windows

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

Linux
macOS

for devlopment

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

depending on connected data-source

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

yes

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

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

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

PL/SQL

yes, depending on connected data-source

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, across time and space (hash partitioning) attributes

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication with hot standby and reads on replicas

Multi-source replication
Source-replica replication

depending on connected data-source

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

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

depending on connected data-source

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

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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More resources

DB-Engines blog posts

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