DBMS > Faircom EDGE vs. Immudb vs. JanusGraph vs. Oracle vs. SAP HANA

System Properties Comparison Faircom EDGE vs. Immudb vs. JanusGraph vs. Oracle vs. SAP HANA

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

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used RDBMS

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store
Relational DBMS

Key-value store

Graph DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.faircom.com/products/faircom-edge

github.com/codenotary/immudb
immudb.io

janusgraph.org

www.oracle.com/database

www.sap.com/products/hana.html

Technical documentation

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

docs.immudb.io

docs.janusgraph.org

docs.oracle.com/en/database

help.sap.com/hana

Developer

FairCom Corporation

Codenotary

Linux Foundation; originally developed as Titan by Aurelius

Oracle

SAP

Initial release

1979

2020

2017

1980

2010

Current release

V3, October 2020

1.2.3, April 2022

0.6.3, February 2023

23c, September 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Appliance or cloud-service

Data scheme

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

schema-free

yes

Schemaless in JSON and XML columns

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

SQL-like syntax

yes

with proprietary extensions

yes

APIs and other access methods

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

gRPC protocol
PostgreSQL wire protocol

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

PL/SQL

also stored procedures in Java possible

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

yes

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