DBMS > Hive vs. Oracle NoSQL vs. RavenDB vs. SQLite

System Properties Comparison Hive vs. Oracle NoSQL vs. RavenDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

hive.apache.org

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

ravendb.net

www.sqlite.org

Technical documentation

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

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

ravendb.net/docs

www.sqlite.org/docs.html

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

Hibernating Rhinos

Dwayne Richard Hipp

Initial release

2012

2011

2010

2000

Current release

3.1.3, April 2022

24.1, May 2024

5.4, July 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

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

Open Source

AGPL version 3, commercial license available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM

Linux
Solaris SPARC/x86

Linux
macOS
Raspberry Pi
Windows

server-less

Data scheme

yes

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

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

optional

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like DML and DDL statements

SQL-like query language (RQL)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++
Java
PHP
Python

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

configurable

ACID within a storage node (=shard)

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

User concepts

Access control

Access rights for users, groups and roles

Access rights for users and roles

Authorization levels configured per client per database

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