DBMS > Drizzle vs. HEAVY.AI vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. SiteWhere

System Properties Comparison Drizzle vs. HEAVY.AI vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. SiteWhere

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Microsofts flagship relational DBMS

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Time Series 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

azure.microsoft.com/services/synapse-analytics

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

github.com/sitewhere/sitewhere

Technical documentation

docs.heavy.ai

docs.microsoft.com/azure/synapse-analytics

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

sitewhere1.sitewhere.io/index.html

Developer

Drizzle project, originally started by Brian Aker

HEAVY.AI, Inc.

Microsoft

SiteWhere

Initial release

2008

2016

1989

2010

Current release

7.2.4, September 2012

5.10, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Common Public Attribution License Version 1.0

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++

C++ and CUDA

C++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

predefined scheme

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

with proprietary extensions

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

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

HTTP REST

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
PHP

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

Server-side scripts

Stored procedures

Transact SQL

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

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding, horizontal partitioning

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

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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