DBMS > Faircom DB vs. Kinetica vs. Percona Server for MongoDB vs. Tibero vs. Typesense

System Properties Comparison Faircom DB vs. Kinetica vs. Percona Server for MongoDB vs. Tibero vs. Typesense

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.

Fully vectorized database across both GPUs and CPUs

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

A secure RDBMS, designed for easy portability from Oracle

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS
Time Series 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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

www.faircom.com/products/faircom-db

www.kinetica.com

www.percona.com/mongodb/software/percona-server-for-mongodb

us.tmaxsoft.com/products/tibero

typesense.org

Technical documentation

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

docs.kinetica.com

docs.percona.com/percona-distribution-for-mongodb

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

typesense.org/docs

Developer

FairCom Corporation

Kinetica

Percona

TmaxSoft

Initial release

1979

2012

2015

2003

2015

Current release

V12, November 2020

7.1, August 2021

3.4.10-2.10, November 2017

6, April 2015

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

GPL Version 2

commercial

Open Source

GPL V3

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++

C, C++

C++

C and Assembler

C++

Server operating systems

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

easily portable to other OSs

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

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

yes

schema-free

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

RESTful HTTP API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

JavaScript

Persistent Stored Procedure (PSM)

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

Sharding

horizontal partitioning

by range, hash, list or composite

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).

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

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

via In-Memory Engine

planned for next version

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

Access rights for users and roles

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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