DBMS > Faircom DB vs. Graphite vs. Kinetica vs. MonetDB vs. RocksDB

System Properties Comparison Faircom DB vs. Graphite vs. Kinetica vs. MonetDB vs. RocksDB

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

Fully vectorized database across both GPUs and CPUs

A relational database management system that stores data in columns

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

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

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

Website

www.faircom.com/products/faircom-db

github.com/graphite-project/graphite-web

www.kinetica.com

www.monetdb.org

rocksdb.org

Technical documentation

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

graphite.readthedocs.io

docs.kinetica.com

www.monetdb.org/Documentation

github.com/facebook/rocksdb/wiki

Developer

FairCom Corporation

Chris Davis

Kinetica

MonetDB BV

Facebook, Inc.

Initial release

1979

2006

2012

2004

2013

Current release

V12, November 2020

7.1, August 2021

Dec2023 (11.49), December 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

BSD

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++

Python

C, C++

C++

Server operating systems

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

easily portable to other OSs

Linux
Unix

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like DML and DDL statements

yes

SQL 2003 with some 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

JDBC
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

C++ API
Java API

Supported programming languages

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

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

yes, in SQL, C, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

Sharding via remote tables

horizontal partitioning

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

Source-replica replication

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

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

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

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

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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