DBMS > Hawkular Metrics vs. ITTIA vs. Microsoft SQL Server vs. Postgres-XL vs. SAP SQL Anywhere

System Properties Comparison Hawkular Metrics vs. ITTIA vs. Microsoft SQL Server vs. Postgres-XL vs. SAP SQL Anywhere

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.

Edge Time Series DBMS with Real-Time Stream Processing

Microsofts flagship relational DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

www.hawkular.org

www.ittia.com

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

www.postgres-xl.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

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

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

www.postgres-xl.org/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Community supported by Red Hat

ITTIA L.L.C.

Microsoft

SAP

formerly Sybase

Initial release

2014

2007

1989

2014

since 2012, originally named StormDB

1992

Current release

8.7

SQL Server 2022, November 2022

10 R1, October 2018

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

HTTP REST

JDBC
ODBC
RESTful HTTP API
WebSocket

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Go
Java
Python
Ruby

C
C++
JavaScript (Node.js)
Python

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

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

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Database file passwords

fine grained access rights according to SQL-standard

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