DBMS > BoltDB vs. Faircom EDGE vs. Google Cloud Firestore vs. OrientDB vs. RocksDB

System Properties Comparison BoltDB vs. Faircom EDGE vs. Google Cloud Firestore vs. OrientDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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.

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Key-value store

Key-value store
Relational DBMS

Document store

Document store
Graph DBMS
Key-value store

Key-value store

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

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

Website

github.com/boltdb/bolt

www.faircom.com/products/faircom-edge

firebase.google.com/products/firestore

orientdb.org

rocksdb.org

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

firebase.google.com/docs/firestore

www.orientdb.com/docs/last/index.html

github.com/facebook/rocksdb/wiki

Developer

FairCom Corporation

Google

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Initial release

2013

1979

2017

2010

2013

Current release

V3, October 2020

3.2.29, March 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Restricted, free version available

commercial

Open Source

Apache version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

hosted

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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

ANSI SQL queries

SQL-like query language, no joins

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes, Firebase Rules & Cloud Functions

Java, Javascript

Triggers

yes

yes, with Cloud Functions

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

relationship in graphs

Transaction concepts

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

yes

ACID

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users and roles; record level security configurable

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