DBMS > Faircom EDGE vs. HugeGraph vs. RocksDB vs. TimesTen

System Properties Comparison Faircom EDGE vs. HugeGraph vs. RocksDB vs. TimesTen

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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

A fast-speed and highly-scalable Graph DBMS

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

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Key-value store

Relational DBMS

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	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.faircom.com/products/faircom-edge

github.com/hugegraph
hugegraph.apache.org

rocksdb.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

hugegraph.apache.org/docs

github.com/facebook/rocksdb/wiki

docs.oracle.com/database/timesten-18.1

Developer

FairCom Corporation

Baidu

Facebook, Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1979

2018

2013

1998

Current release

V3, October 2020

0.9

9.2.1, May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

BSD

commercial

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++

Java

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Unix

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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

yes

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

also supports composite index and range index

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

Java API
RESTful HTTP API
TinkerPop Gremlin

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Groovy
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

asynchronous Gremlin script jobs

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

when using SQL

yes

edges in graph

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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.

Users, roles and permissions

fine grained access rights according to SQL-standard

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