DBMS > HEAVY.AI vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. Netezza vs. SAP SQL Anywhere

System Properties Comparison HEAVY.AI vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. Netezza vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

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

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

www.ibm.com/products/netezza

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

Technical documentation

docs.heavy.ai

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

help.sap.com/docs/SAP_SQL_Anywhere

Developer

HEAVY.AI, Inc.

Microsoft

IBM

SAP

formerly Sybase

Initial release

2016

2012

1989

2000

1992

Current release

5.10, January 2022

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

C++

Server operating systems

Linux

hosted

Linux
Windows

Linux

included in appliance

AIX
HP-UX
Linux
OS X
Solaris
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

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

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

JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

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

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

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

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

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

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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