DBMS > Oracle NoSQL vs. Riak KV vs. SQLite vs. TinkerGraph

System Properties Comparison Oracle NoSQL vs. Riak KV vs. SQLite vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

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

Distributed, fault tolerant key-value store

Widely used embeddable, in-process RDBMS

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Key-value store
Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Graph DBMS

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

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

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

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

www.sqlite.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

www.tiot.jp/riak-docs/riak/kv/latest

www.sqlite.org/docs.html

Developer

Oracle

OpenSource, formerly Basho Technologies

Dwayne Richard Hipp

Initial release

2011

2009

2000

2009

Current release

24.1, May 2024

3.2.0, December 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

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

Open Source

Apache version 2, commercial enterprise edition

Open Source

Public Domain

Open Source

Apache 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

Erlang

Java

Server operating systems

Linux
Solaris SPARC/x86

Linux
OS X

server-less

Data scheme

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

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

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

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

TinkerPop 3

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Groovy
Java

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

none

Foreign keys

Referential integrity

links between data sets can be stored

yes

Relationships in graphs

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

optional

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 and roles

yes, using Riak Security

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