DBMS > Oracle NoSQL vs. PlanetScale vs. Riak KV vs. VelocityDB

System Properties Comparison Oracle NoSQL vs. PlanetScale vs. Riak KV vs. VelocityDB

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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

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Distributed, fault tolerant key-value store

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

Key-value store

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

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS
	#21	Object oriented DBMS

Website

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

planetscale.com

velocitydb.com

Technical documentation

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

planetscale.com/docs

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

velocitydb.com/UserGuide

Developer

Oracle

PlanetScale

OpenSource, formerly Basho Technologies

VelocityDB Inc

Initial release

2011

2020

2009

2011

Current release

24.1, May 2024

3.2.0, December 2022

7.x

License

Commercial or Open Source

Open Source

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

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

Linux
Solaris SPARC/x86

Docker
Linux
macOS

Linux
OS X

Any that supports .NET

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

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

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API
Native Erlang Interface

.Net

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

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

Multi-source replication
Source-replica replication

selectable replication factor

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 across shards
Immediate Consistency within a shard

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between data sets can be stored

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

yes, using Riak Security

Based on Windows Authentication

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