DBMS > Amazon Neptune vs. Apache Druid vs. Cassandra vs. GigaSpaces vs. SAP SQL Anywhere

System Properties Comparison Amazon Neptune vs. Apache Druid vs. Cassandra vs. GigaSpaces vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Wide column store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Graph DBMS
Search engine

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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

aws.amazon.com/neptune

druid.apache.org

cassandra.apache.org

www.gigaspaces.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

aws.amazon.com/neptune/developer-resources

druid.apache.org/docs/latest/design

cassandra.apache.org/doc/latest

docs.gigaspaces.com/latest/landing.html

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Amazon

Apache Software Foundation and contributors

Apache Software Foundation

Apache top level project, originally developped by Facebook

Gigaspaces Technologies

SAP

formerly Sybase

Initial release

2017

2012

2008

2000

1992

Current release

29.0.1, April 2024

4.1.3, July 2023

15.5, September 2020

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache version 2

Open Source

Apache Version 2; Commercial licenses available

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

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Unix

BSD
Linux
OS X
Windows

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-less columns are supported

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL for querying

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

SQL-99 for query and DML statements

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
RESTful HTTP/JSON API

Proprietary protocol

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C++
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

Sharding

no "single point of failure"

Sharding

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.

yes, via HDFS, S3 or other storage engines

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

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

Consistency level configurable: ALL, QUORUM, ANY

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

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)

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per object

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

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...
» more

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.