DBMS > Amazon Neptune vs. Google Cloud Firestore vs. Microsoft Access vs. Snowflake vs. STSdb

System Properties Comparison Amazon Neptune vs. Google Cloud Firestore vs. Microsoft Access vs. Snowflake vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

aws.amazon.com/neptune

firebase.google.com/products/firestore

www.microsoft.com/en-us/microsoft-365/access

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

aws.amazon.com/neptune/developer-resources

firebase.google.com/docs/firestore

developer.microsoft.com/en-us/access

docs.snowflake.net/manuals/index.html

Developer

Amazon

Google

Microsoft

Snowflake Computing Inc.

STS Soft SC

Initial release

2017

1992

2014

2011

Current release

1902 (16.0.11328.20222), March 2019

4.0.8, September 2015

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Open Source

GPLv2, commercial license available

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

Windows

Not a real database server, but making use of DLLs

hosted

Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

but not compliant to any SQL standard

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes, with Cloud Functions

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication

none

yes

none

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

Relationships in graphs

yes

Transaction concepts

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

ACID

yes

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

but no files for transaction logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and 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.

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept, user roles and pluggable authentication

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