DBMS > Faircom EDGE vs. H2GIS vs. Informix vs. Manticore Search vs. SiriDB

System Properties Comparison Faircom EDGE vs. H2GIS vs. Informix vs. Manticore Search vs. SiriDB

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

Spatial extension of H2

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

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

Open Source Time Series DBMS

Primary database model

Key-value store
Relational DBMS

Spatial DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Search engine

Time Series DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

www.faircom.com/products/faircom-edge

www.h2gis.org

www.ibm.com/products/informix

manticoresearch.com

siridb.com

Technical documentation

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

www.h2gis.org/docs/home

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

manual.manticoresearch.com

docs.siridb.com

Developer

FairCom Corporation

CNRS

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Manticore Software

Cesbit

Initial release

1979

2013

1984

2017

Current release

V3, October 2020

14.10.FC5, November 2020

6.0, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

LGPL 3.0

commercial

free developer edition available

Open Source

GPL version 2

Open Source

MIT License

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, C++ and Java

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux

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

Since Version 12.10 support for JSON/BSON datatypes

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

yes

Numeric data

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

yes

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
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

HTTP API

Supported programming languages

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

Java

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

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

based on H2

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

based on H2

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

yes

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.

yes

based on H2

Users with fine-grained authentication, authorization, and auditing controls

simple rights management via user accounts

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