DBMS > Amazon DocumentDB vs. Hawkular Metrics vs. Microsoft Azure SQL Database vs. SAP HANA

System Properties Comparison Amazon DocumentDB vs. Hawkular Metrics vs. Microsoft Azure SQL Database vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

aws.amazon.com/documentdb

www.hawkular.org

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

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/documentdb/resources

www.hawkular.org/hawkular-metrics/docs/user-guide

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

help.sap.com/hana

Developer

Community supported by Red Hat

Microsoft

SAP

Initial release

2019

2014

2010

Current release

V12

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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
Windows

hosted

Appliance or cloud-service

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP REST

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Java
Python
Ruby

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

Server-side scripts

Stored procedures

Transact SQL

SQLScript, R

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

based on Cassandra

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

yes

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