DBMS > Faircom EDGE vs. ObjectBox vs. Splunk vs. SQLite vs. Trafodion

System Properties Comparison Faircom EDGE vs. ObjectBox vs. Splunk vs. SQLite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Extremely fast embedded database for small devices, IoT and Mobile

Analytics Platform for Big Data

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store
Relational DBMS

Object oriented DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

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	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.faircom.com/products/faircom-edge

Technical documentation

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

docs.objectbox.io

docs.splunk.com/Documentation/Splunk

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

Developer

FairCom Corporation

ObjectBox Limited

Splunk Inc.

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Initial release

1979

2017

2003

2000

2014

Current release

V3, October 2020

3.46.0 (23 May 2024), May 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache License 2.0

commercial

Limited free edition and free developer edition available

Open Source

Public Domain

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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++

C++, Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Android
iOS
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

server-less

Linux

Data scheme

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

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

not rigid because of 'dynamic typing' concept.

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

Splunk Search Processing Language for search commands

yes

SQL-92 is not fully supported

yes

APIs and other access methods

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

Proprietary native API

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

Supported programming languages

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C#
Java
JavaScript
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

online/offline synchronization between client and server

Multi-source replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

via file-system locks

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.

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

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