DBMS > Google Cloud Datastore vs. Google Cloud Firestore vs. Microsoft Access vs. RocksDB vs. Stardog

System Properties Comparison Google Cloud Datastore vs. Google Cloud Firestore vs. Microsoft Access vs. RocksDB vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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.)

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cloud.google.com/datastore

firebase.google.com/products/firestore

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

rocksdb.org

www.stardog.com

Technical documentation

cloud.google.com/datastore/docs

firebase.google.com/docs/firestore

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

docs.stardog.com

Developer

Google

Microsoft

Facebook, Inc.

Stardog-Union

Initial release

2008

2017

1992

2013

2010

Current release

1902 (16.0.11328.20222), March 2019

8.11.4, April 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

BSD

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes, details here

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

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

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes, Firebase Rules & Cloud Functions

yes

since Access 2010 using the ACE-engine

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Callbacks using the Google Apps Engine

yes, with Cloud Functions

yes

since Access 2010 using the ACE-engine

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Multi-source replication

none

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

relationships in graphs

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

yes

ACID

but no files for transaction logging

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud 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

Access rights for users and roles

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