DBMS > Amazon SimpleDB vs. Hawkular Metrics vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Amazon SimpleDB vs. Hawkular Metrics vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

Globally distributed, horizontally scalable, multi-model database service

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Key-value store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

aws.amazon.com/simpledb

www.hawkular.org

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.aws.amazon.com/simpledb

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

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

Developer

Amazon

Community supported by Red Hat

Microsoft

Initial release

2007

2014

2016

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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.

Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All columns are indexed automatically

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Java
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
PHP

Server-side scripts

Stored procedures

JavaScript

Transact SQL

Triggers

yes

via Hawkular Alerting

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

Concurrent data updates can be detected by the application

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

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

Access rights can be defined down to the item level

yes

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