DBMS > Amazon Redshift vs. Apache Phoenix vs. Neo4j vs. Sadas Engine vs. Yanza

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. Neo4j vs. Sadas Engine vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Time Series DBMS for IoT Applications

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

aws.amazon.com/redshift

phoenix.apache.org

neo4j.com

www.sadasengine.com

yanza.com

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

neo4j.com/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Neo4j, Inc.

SADAS s.r.l.

Yanza

Initial release

2012

2014

2007

2006

2015

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

5.20, May 2024

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL version3, commercial licenses available

commercial

free trial version available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

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

Java, Scala

C++

Server operating systems

hosted

Linux
Unix
Windows

Linux

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

AIX
Linux
Windows

Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free and schema-optional

yes

schema-free

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

restricted

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

JDBC
ODBC
Proprietary protocol

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

User defined Procedures and Functions

Triggers

yes

via event handler

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes using Neo4j Fabric

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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