DBMS > Google BigQuery vs. Google Cloud Firestore vs. Graphite vs. Microsoft Azure SQL Database vs. SAP SQL Anywhere

System Properties Comparison Google BigQuery vs. Google Cloud Firestore vs. Graphite vs. Microsoft Azure SQL Database vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Database as a Service offering with high compatibility to Microsoft SQL Server

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

cloud.google.com/bigquery

firebase.google.com/products/firestore

github.com/graphite-project/graphite-web

azure.microsoft.com/en-us/products/azure-sql/database

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

cloud.google.com/bigquery/docs

firebase.google.com/docs/firestore

graphite.readthedocs.io

docs.microsoft.com/en-us/azure/azure-sql

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

Chris Davis

Microsoft

SAP

formerly Sybase

Initial release

2010

2017

2006

2010

1992

Current release

V12

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Python

C++

Server operating systems

hosted

Linux
Unix

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

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

HTTP API
Sockets

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes, Firebase Rules & Cloud Functions

Transact SQL

yes, in C/C++, Java, .Net or Perl

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes, with always 3 replicas available

Source-replica replication

Database mirroring

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

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