DBMS > Amazon Neptune vs. Cassandra vs. H2 vs. Netezza

System Properties Comparison Amazon Neptune vs. Cassandra vs. H2 vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Graph DBMS
RDF store

Wide column store

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

aws.amazon.com/neptune

cassandra.apache.org

www.h2database.com

www.ibm.com/products/netezza

Technical documentation

aws.amazon.com/neptune/developer-resources

cassandra.apache.org/doc/latest

www.h2database.com/html/main.html

Developer

Amazon

Apache Software Foundation

Apache top level project, originally developped by Facebook

Thomas Mueller

IBM

Initial release

2017

2008

2005

2000

Current release

4.1.3, July 2023

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

hosted

BSD
Linux
OS X
Windows

All OS with a Java VM

Linux

included in appliance

Data scheme

schema-free

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

selectable replication factor

Representation of geographical distribution of servers is possible

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

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
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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