DBMS > Google Cloud Firestore vs. JanusGraph vs. Microsoft Access vs. Snowflake vs. TerarkDB

System Properties Comparison Google Cloud Firestore vs. JanusGraph vs. Microsoft Access vs. Snowflake vs. TerarkDB

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.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

firebase.google.com/products/firestore

janusgraph.org

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

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

firebase.google.com/docs/firestore

docs.janusgraph.org

developer.microsoft.com/en-us/access

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Google

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2017

1992

2014

2016

Current release

0.6.3, February 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

commercial

restricted open source version 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

Java

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

schema-free

yes

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

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

but not compliant to any SQL standard

yes

APIs and other access methods

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

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

Clojure
Java
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

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

yes

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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. Security Rules for 3rd party authentication using Firebase Auth.

User authentification and security via Rexster Graph Server

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

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.