DBMS > Google Cloud Firestore vs. Microsoft Azure Synapse Analytics vs. MonetDB vs. TimesTen vs. VoltDB

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure Synapse Analytics vs. MonetDB vs. TimesTen vs. VoltDB

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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A relational database management system that stores data in columns

In-Memory RDBMS compatible to Oracle

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Relational DBMS

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	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

firebase.google.com/products/firestore

azure.microsoft.com/services/synapse-analytics

www.monetdb.org

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

www.voltdb.com

Technical documentation

firebase.google.com/docs/firestore

docs.microsoft.com/azure/synapse-analytics

www.monetdb.org/Documentation

docs.oracle.com/database/timesten-18.1

docs.voltdb.com

Developer

Google

Microsoft

MonetDB BV

Oracle, TimesTen Performance Software, HP

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

VoltDB Inc.

Initial release

2017

2016

2004

1998

2010

Current release

Dec2023 (11.49), December 2023

11 Release 2 (11.2.2.8.0)

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X

for development

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

SQL 2003 with some extensions

yes

only a subset of SQL 99

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C#
Java
PHP

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++
Java
PL/SQL

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Transact SQL

yes, in SQL, C, R

PL/SQL

Java

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding via remote tables

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

Source-replica replication available in experimental status

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

Snapshots and command logging

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.

yes

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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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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