DBMS > Microsoft Azure Table Storage vs. NuoDB vs. Riak KV vs. RocksDB vs. SQLite

System Properties Comparison Microsoft Azure Table Storage vs. NuoDB vs. Riak KV vs. RocksDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A Wide Column Store for rapid development using massive semi-structured datasets

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Distributed, fault tolerant key-value store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Widely used embeddable, in-process RDBMS

Primary database model

Wide column store

Relational DBMS

Key-value store

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

Key-value store

Relational DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

azure.microsoft.com/en-us/services/storage/tables

www.3ds.com/nuodb-distributed-sql-database

rocksdb.org

www.sqlite.org

Technical documentation

doc.nuodb.com

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

github.com/facebook/rocksdb/wiki

www.sqlite.org/docs.html

Developer

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

OpenSource, formerly Basho Technologies

Facebook, Inc.

Dwayne Richard Hipp

Initial release

2012

2013

2009

2013

2000

Current release

3.2.0, December 2022

9.2.1, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache version 2, commercial enterprise edition

Open Source

BSD

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

C++

Server operating systems

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X

Linux

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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

restricted

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

C++ API
Java API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

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

C
C++
Go
Java
Perl
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

Java, SQL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

Sharding

no "single point of failure"

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Managed transparently by NuoDB

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

optimistic locking

ACID

tunable commit protocol

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Standard SQL roles/ privileges, Administrative Users

yes, using Riak Security

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