DBMS > Amazon Neptune vs. Amazon Redshift vs. Apache Druid vs. Sadas Engine vs. Sequoiadb

System Properties Comparison Amazon Neptune vs. Amazon Redshift vs. Apache Druid vs. Sadas Engine vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Large scale data warehouse service for use with business intelligence tools

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

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

NewSQL database with distributed OLTP and SQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Relational 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	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

aws.amazon.com/neptune

aws.amazon.com/redshift

druid.apache.org

www.sadasengine.com

www.sequoiadb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

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

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

SADAS s.r.l.

Sequoiadb Ltd.

Initial release

2017

2012

2006

2013

Current release

29.0.1, April 2024

8.0

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

free trial version available

Open Source

Server: AGPL; Client: Apache V2

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.

Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Unix

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

yes

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

proprietary protocol using JSON

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

horizontal partitioning

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.

yes

yes, via HDFS, S3 or other storage engines

none

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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

managed by 'Learn by Usage'

User concepts

Access control

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

fine grained access rights according to SQL-standard

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

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

simple password-based access control

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