DBMS > HBase vs. Microsoft SQL Server vs. Quasardb vs. Riak KV vs. Sadas Engine

System Properties Comparison HBase vs. Microsoft SQL Server vs. Quasardb vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

hbase.apache.org

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

quasar.ai

www.sadasengine.com

Technical documentation

hbase.apache.org/book.html

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

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/kv/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

quasardb

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Initial release

2008

1989

2009

2006

Current release

2.3.4, January 2021

SQL Server 2022, November 2022

3.14.1, January 2024

3.2.0, December 2022

8.0

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Erlang

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
Windows

BSD
Linux
OS X
Windows

Linux
OS X

AIX
Linux
Windows

Data scheme

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

integer and binary

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

with tags

restricted

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

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

HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

consistent hashing

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

managed by 'Learn by Usage'

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

yes, using Riak Security

Access rights for users, groups and roles according to SQL-standard

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