DBMS > Apache Doris vs. Faircom DB vs. NCache vs. Oracle

System Properties Comparison Apache Doris vs. Faircom DB vs. NCache vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

Open-Source and Enterprise in-memory Key-Value Store

Widely used RDBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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	0.57
Rank	#244	Overall
	#113	Relational DBMS

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

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

www.faircom.com/products/faircom-db

www.alachisoft.com/ncache

www.oracle.com/database

Technical documentation

github.com/apache/doris/wiki

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

www.alachisoft.com/resources/docs

docs.oracle.com/en/database

Developer

Apache Software Foundation, originally contributed from Baidu

FairCom Corporation

Alachisoft

Oracle

Initial release

2017

1979

2005

1980

Current release

1.2.2, February 2023

V12, November 2020

5.3.3, April 2024

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Enterprise Edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

ANSI C, C++

C#, .NET, .NET Core, Java

C and C++

Server operating systems

Linux

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

easily portable to other OSs

Linux
Windows

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

Data scheme

yes

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

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

yes, ANSI SQL with proprietary extensions

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

with proprietary extensions

APIs and other access methods

JDBC
MySQL client

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

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

support for stored procedures with SQL-Server CLR

PL/SQL

also stored procedures in Java possible

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes, with selectable consistency level

Multi-source replication
Source-replica replication

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

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

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

optimistic locking and pessimistic locking

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'

User concepts

Access control

fine grained access rights according to SQL-standard

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

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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