DBMS > Faircom DB vs. Hive vs. LeanXcale vs. Oracle NoSQL

System Properties Comparison Faircom DB vs. Hive vs. LeanXcale vs. Oracle NoSQL

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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 warehouse software for querying and managing large distributed datasets, built on Hadoop

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store
Key-value store
Relational 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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.faircom.com/products/faircom-db

hive.apache.org

www.leanxcale.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

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

cwiki.apache.org/confluence/display/Hive/Home

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

FairCom Corporation

Apache Software Foundation

initially developed by Facebook

LeanXcale

Oracle

Initial release

1979

2012

2015

2011

Current release

V12, November 2020

3.1.3, April 2022

23.3, December 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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++

Java

Server operating systems

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

easily portable to other OSs

All OS with a Java VM

Linux
Solaris SPARC/x86

Data scheme

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

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

optional

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

through Apache Derby

SQL-like DML and DDL statements

APIs and other access methods

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

JDBC
ODBC
Thrift

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

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

C++
Java
PHP
Python

C
Java
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

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).

selectable replication factor

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate 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

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

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

Access rights for users, groups and roles

Access rights for users and roles

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More resources

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