DBMS > HBase vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. Splice Machine

System Properties Comparison HBase vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

hbase.apache.org

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

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

splicemachine.com

Technical documentation

hbase.apache.org/book.html

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

help.sap.com/docs/SAP_SQL_Anywhere

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

SAP

formerly Sybase

Splice Machine

Initial release

2008

1989

1992

2014

Current release

2.3.4, January 2021

SQL Server 2022, November 2022

17, July 2015

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

commercial

Open Source

AGPL 3.0, commercial license available

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++

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

Java API
RESTful HTTP API
Thrift

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

ADO.NET
HTTP API
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

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

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

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

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Shared Nothhing Auto-Sharding, Columnar 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

Database mirroring

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

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

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