DBMS > Faircom EDGE vs. H2 vs. ITTIA vs. Manticore Search vs. STSdb

System Properties Comparison Faircom EDGE vs. H2 vs. ITTIA vs. Manticore Search vs. STSdb

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.

Edge Time Series DBMS with Real-Time Stream Processing

Multi-storage database for search, including full-text search.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS

Time Series DBMS

using the Manticore Columnar Library

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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.faircom.com/products/faircom-edge

www.h2database.com

www.ittia.com

manticoresearch.com

github.com/STSSoft/STSdb4

Technical documentation

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

www.h2database.com/html/main.html

manual.manticoresearch.com

Developer

FairCom Corporation

Thomas Mueller

ITTIA L.L.C.

Manticore Software

STS Soft SC

Initial release

1979

2005

2007

2017

2011

Current release

V3, October 2020

2.2.220, July 2023

8.7

6.0, February 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

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

commercial

Open Source

GPL version 2

Open Source

GPLv2, 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

C and C++

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

Linux
Windows

FreeBSD
Linux
macOS
Windows

Windows

Data scheme

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

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

primitive types and user defined types (classes)

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

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

ANSI SQL queries

yes

SQL-like query language

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
ODBC
RESTful HTTP API
WebSocket

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

.NET Client API

Supported programming languages

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

Java

C
C++
JavaScript (Node.js)
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java Stored Procedures and User-Defined Functions

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

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

yes

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Database file passwords

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