DBMS > Firebolt vs. LeanXcale vs. Oracle NoSQL vs. OushuDB

System Properties Comparison Firebolt vs. LeanXcale vs. Oracle NoSQL vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	1.90
Rank	#134	Overall
	#62	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

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Website

www.firebolt.io

www.leanxcale.com

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

www.oushu.com/product/oushuDB

Technical documentation

docs.firebolt.io

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

www.oushu.com/documentation

Developer

Firebolt Analytics Inc.

LeanXcale

Oracle

Oushu

Initial release

2020

2015

2011

Current release

23.3, December 2023

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux
Solaris SPARC/x86

Linux

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

optional

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

through Apache Derby

SQL-like DML and DDL statements

Full-featured ANSI SQL support

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Go
JavaScript (Node.js)
Python

C
Java
Scala

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

C
C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users and roles

Kerberos, SSL and role based access

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More resources

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