DBMS > Amazon Aurora vs. Dgraph vs. Google Cloud Firestore vs. Microsoft SQL Server vs. searchxml

System Properties Comparison Amazon Aurora vs. Dgraph vs. Google Cloud Firestore vs. Microsoft SQL Server vs. searchxml

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Distributed and scalable native Graph DBMS

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.

Microsofts flagship relational DBMS

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Native XML DBMS
Search engine

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

aws.amazon.com/rds/aurora

dgraph.io

firebase.google.com/products/firestore

www.microsoft.com/en-us/sql-server

www.searchxml.net/category/products

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

dgraph.io/docs

firebase.google.com/docs/firestore

learn.microsoft.com/en-US/sql/sql-server

www.searchxml.net/support/handouts

Developer

Amazon

Dgraph Labs, Inc.

Google

Microsoft

informationpartners gmbh

Initial release

2015

2016

2017

1989

2015

Current release

SQL Server 2022, November 2022

1.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
Windows

Windows

Data scheme

yes

schema-free

yes

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

on the application server

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

sychronisation to multiple collections

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Planned for future releases

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

Domain, group and role-based access control at the document level and for application services

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