DBMS > Hawkular Metrics vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OpenTSDB vs. YottaDB

System Properties Comparison Hawkular Metrics vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OpenTSDB vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

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

A Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

Scalable Time Series DBMS based on HBase

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.hawkular.org

azure.microsoft.com/en-us/services/storage/tables

www.microsoft.com/en-us/sql-server

opentsdb.net

yottadb.com

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

opentsdb.net/docs/build/html/index.html

yottadb.com/resources/documentation

Developer

Community supported by Red Hat

Microsoft

currently maintained by Yahoo and other contributors

YottaDB, LLC

Initial release

2014

2012

1989

2011

2001

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

LGPL

Open Source

AGPL 3.0

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.

SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux
Windows

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

by using the Octo plugin

APIs and other access methods

HTTP REST

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Telnet API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Go
Java
Python
Ruby

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Erlang
Go
Java
Python
R
Ruby

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

optimistic locking

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 based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

More information provided by the system vendor

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.