DBMS > Faircom EDGE vs. Google Cloud Firestore vs. ObjectBox vs. SAP Adaptive Server vs. TimesTen

System Properties Comparison Faircom EDGE vs. Google Cloud Firestore vs. ObjectBox vs. SAP Adaptive Server vs. TimesTen

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.

Extremely fast embedded database for small devices, IoT and Mobile

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store
Relational DBMS

Document store

Object oriented DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.faircom.com/products/faircom-edge

firebase.google.com/products/firestore

objectbox.io

www.sap.com/products/technology-platform/sybase-ase.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

firebase.google.com/docs/firestore

docs.objectbox.io

help.sap.com/docs/SAP_ASE

docs.oracle.com/database/timesten-18.1

Developer

FairCom Corporation

Google

ObjectBox Limited

SAP, Sybase

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1979

2017

1987

1998

Current release

V3, October 2020

16.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache License 2.0

commercial

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

ANSI C, C++

C and C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Android
iOS
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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

schema-free

yes

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

yes

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

Proprietary native API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C++
Cobol
Java
Java
Perl
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes, Firebase Rules & Cloud Functions

Java and Transact-SQL

PL/SQL

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

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
Tunable Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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.

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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