DBMS > Faircom EDGE vs. H2 vs. Splice Machine

System Properties Comparison Faircom EDGE vs. H2 vs. Splice Machine

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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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.03
Rank	#394	Overall
	#61	Key-value stores
	#162	Relational DBMS

Score	9.01
Rank	#52	Overall
	#33	Relational DBMS

Score	0.83
Rank	#253	Overall
	#116	Relational DBMS

Website

www.faircom.com/products/faircomedge-iot-database

www.h2database.com

splicemachine.com

Technical documentation

learn.faircomcorp.com/developers/documentation_directory

www.h2database.com/html/main.html

doc.splicemachine.com

Developer

FairCom Corporation

Thomas Mueller

Splice Machine

Initial release

1979

2005

2014

Current release

V3, October 2020

2.1.214, June 2022

3.1, March 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

AGPL 3.0, commercial license available

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++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

Flexible Schema (defined schema, partial schema, 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

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

Java

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java Stored Procedures and User-Defined Functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable 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

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes, multi-version concurrency control (MVCC)

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.

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

Recent citations in the news

Data Technology Company FairCom Expands The Edge with 2 New Releases of its Edge Computing Products
19 April 2023, Business Wire

World's First Converged IIoT Hub to be Showcased at IoT Tech Expo
3 September 2021, Automation.com

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

Shane Johnson Joins FairCom as Head of Marketing
16 June 2021, The Fast Mode

FairCom EDGE | Database for IoT | FairCom
20 April 2023, faircom.com

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to ...
19 January 2021, PR Newswire

Splice Machine Readies Cloud Big Data Service -- ADTmag
8 February 2017, ADT Magazine

Splice Machine Launches Feature Store to Simplify Feature ...
19 January 2021, Datanami

Supercharge Your Database with Language AI
4 April 2023, RTInsights

provided by Google News

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