DBMS > Faircom DB vs. Graphite vs. MarkLogic vs. MySQL vs. Oracle Coherence

System Properties Comparison Faircom DB vs. Graphite vs. MarkLogic vs. MySQL vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

Oracles in-memory data grid solution

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

www.faircom.com/products/faircom-db

github.com/graphite-project/graphite-web

www.marklogic.com

www.mysql.com

www.oracle.com/java/coherence

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

graphite.readthedocs.io

docs.marklogic.com

dev.mysql.com/doc

docs.oracle.com/en/middleware/standalone/coherence

Developer

FairCom Corporation

Chris Davis

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Initial release

1979

2006

2001

1995

2007

Current release

V12, November 2020

11.0, December 2022

8.4.0, April 2024

14.1, August 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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++

Python

C++

C and C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
Unix

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

Schema can be enforced

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

Numeric data only

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 with proprietary extensions

yes

SQL92

yes

with proprietary extensions

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API
Sockets

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

JavaScript (Node.js)
Python

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via XQuery or JavaScript

yes

proprietary syntax

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

yes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

can act as a resource manager in an XA/JTA transaction

ACID

not for MyISAM storage engine

configurable

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

optionally

In-memory capabilities

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

yes

yes, with Range Indexes

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

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