DBMS > Amazon Neptune vs. Cassandra vs. IBM Db2 warehouse vs. Microsoft Azure Table Storage vs. Realm

System Properties Comparison Amazon Neptune vs. Cassandra vs. IBM Db2 warehouse vs. Microsoft Azure Table Storage vs. Realm

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

Cloud-based data warehousing service

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

aws.amazon.com/neptune

cassandra.apache.org

www.ibm.com/products/db2/warehouse

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

realm.io

Technical documentation

aws.amazon.com/neptune/developer-resources

cassandra.apache.org/doc/latest

realm.io/docs

Developer

Amazon

Apache Software Foundation

Apache top level project, originally developped by Facebook

IBM

Microsoft

Realm, acquired by MongoDB in May 2019

Initial release

2017

2008

2014

2012

2014

Current release

4.1.3, July 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

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

hosted

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

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.

Import/export of XML data possible

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

.NET Client API
JDBC
ODBC
OLE DB

RESTful HTTP API

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
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

PL/SQL, SQL PL

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

none

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

yes

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

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
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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

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

Access rights based on private key authentication or shared access signatures

yes

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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