DBMS > Faircom EDGE vs. Ignite vs. InfinityDB vs. RocksDB

System Properties Comparison Faircom EDGE vs. Ignite vs. InfinityDB vs. RocksDB

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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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A Java embedded Key-Value Store which extends the Java Map interface

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store
Relational DBMS

Key-value store

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

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.faircom.com/products/faircom-edge

ignite.apache.org

boilerbay.com

rocksdb.org

Technical documentation

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

apacheignite.readme.io/docs

boilerbay.com/infinitydb/manual

github.com/facebook/rocksdb/wiki

Developer

FairCom Corporation

Apache Software Foundation

Boiler Bay Inc.

Facebook, Inc.

Initial release

1979

2015

2002

2013

Current release

V3, October 2020

Apache Ignite 2.6

4.0

8.11.4, April 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++, Java, .Net

Java

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

Data scheme

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

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

ANSI SQL queries

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

C++ API
Java API

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes (replicated cache)

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

when using SQL

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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.

Security Hooks for custom implementations

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