DBMS > Amazon Redshift vs. atoti vs. Kyligence Enterprise vs. Microsoft Azure SQL Database vs. OrigoDB

System Properties Comparison Amazon Redshift vs. atoti vs. Kyligence Enterprise vs. Microsoft Azure SQL Database vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A distributed analytics engine for big data, built on top of Apache Kylin

Database as a Service offering with high compatibility to Microsoft SQL Server

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

aws.amazon.com/redshift

atoti.io

kyligence.io/kyligence-enterprise

azure.microsoft.com/en-us/products/azure-sql/database

origodb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.atoti.io

docs.microsoft.com/en-us/azure/azure-sql

origodb.com/docs

Developer

Amazon (based on PostgreSQL)

ActiveViam

Kyligence, Inc.

Microsoft

Robert Friberg et al

Initial release

2012

2016

2010

2009

under the name LiveDB

Current release

V12

License

Commercial or Open Source

commercial

free versions available

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.

Implementation language

Java

C++

Server operating systems

hosted

Linux

hosted

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

yes

can be achieved using .NET

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Multidimensional Expressions (MDX)

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net

Server-side scripts

Stored procedures

user defined functions

in Python

Python

Transact SQL

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based authorization

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