DBMS > Microsoft Azure Table Storage vs. Neo4j vs. VoltDB

System Properties Comparison Microsoft Azure Table Storage vs. Neo4j vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Wide column store

Graph DBMS

Relational DBMS

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

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	44.47
Rank	#23	Overall
	#1	Graph DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

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

neo4j.com

www.voltdb.com

Technical documentation

neo4j.com/docs

docs.voltdb.com

Developer

Microsoft

Neo4j, Inc.

VoltDB Inc.

Initial release

2012

2007

2010

Current release

5.19, April 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

GPL version3, commercial licenses available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java, Scala

Java, C++

Server operating systems

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

schema-free

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

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

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

Java

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes using Neo4j Fabric

Sharding

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.

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Foreign keys

Referential integrity

yes

Relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

optimistic locking

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

This Week in Neo4j: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more
27 April 2024

GQL is Here: Your Cypher Queries in a GQL World
26 April 2024

GQL: The ISO Standard for Graphs Has Arrived
25 April 2024

What Is Retrieval-Augmented Generation (RAG)?
24 April 2024

This Week in Neo4j: Google Cloud, Analysis, Knowledge Graph, Relationships and more
20 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Applying Graph Analytics to Game of Thrones
12 June 2019, Amy Hodler & Mark Needham, Neo4j (guest author)

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

The openCypher Project: Help Shape the SQL for Graphs
22 December 2015, Emil Eifrem (guest author)

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Recent citations in the news

Azure Cosmos DB Data Migration tool imports from Azure Table storage | Azure updates
5 May 2015, azure.microsoft.com

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

Testing Precompiled Azure Functions Locally with Storage Emulator
8 March 2018, Visual Studio Magazine

provided by Google News

Neo4j CTO says new Graph Query Language standard will have 'massive ripple effects'
27 April 2024, SiliconANGLE News

Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English
26 March 2024, PR Newswire

Using Neo4j’s graph database for AI in Azure
4 April 2024, InfoWorld

Neo4j Is Planning IPO on Nasdaq, Largest Owner Greenbridge Says
15 February 2024, Bloomberg

Leveraging Neo4j and Amazon Bedrock for an Explainable, Secure, and Connected Generative AI Solution | Amazon ...
10 November 2023, AWS Blog

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16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

provided by Google News

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