DBMS > Databend vs. Hawkular Metrics vs. Microsoft SQL Server vs. Valentina Server

System Properties Comparison Databend vs. Hawkular Metrics vs. Microsoft SQL Server vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Microsofts flagship relational DBMS

Object-relational database and reports server

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.hawkular.org

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

www.valentina-db.net

Technical documentation

docs.databend.com

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

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Databend Labs

Community supported by Red Hat

Microsoft

Paradigma Software

Initial release

2021

2014

1989

1999

Current release

1.0.59, April 2023

SQL Server 2022, November 2022

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

Java

C++

Server operating systems

hosted
Linux
macOS

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

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

CLI Client
JDBC
RESTful HTTP API

HTTP REST

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

ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Go
Java
Python
Ruby

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

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

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Transaction concepts

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

yes

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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