DBMS > Apache Kylin vs. Faircom DB vs. Oracle vs. TerarkDB vs. Tkrzw

System Properties Comparison Apache Kylin vs. Faircom DB vs. Oracle vs. TerarkDB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Widely used RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

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

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

Score	1.20
Rank	#175	Overall
	#80	Relational DBMS

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Score	0.09
Rank	#354	Overall
	#51	Key-value stores

Website

kylin.apache.org

www.faircom.com/products/faircom-db

www.oracle.com/database

github.com/bytedance/terarkdb

dbmx.net/tkrzw

Technical documentation

kylin.apache.org/docs

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

docs.oracle.com/en/database

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation, originally contributed from eBay Inc

FairCom Corporation

Oracle

ByteDance, originally Terark

Mikio Hirabayashi

Initial release

2015

1979

1980

2016

2020

Current release

3.1.0, July 2020

V12, November 2020

23c, September 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

commercial

restricted free version is available

commercial

restricted open source version available

Open Source

Apache Version 2.0

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

Java

ANSI C, C++

C and C++

C++

Server operating systems

Linux

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

easily portable to other OSs

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

Linux
macOS

Data scheme

yes

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

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

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

ANSI SQL for queries (using Apache Calcite)

yes, ANSI SQL with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

C++ API
Java API

Supported programming languages

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

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

C++
Java

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

PL/SQL

also stored procedures in Java possible

Triggers

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

none

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).

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

yes

using specific database classes

User concepts

Access control

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

fine grained access rights according to SQL-standard

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