DBMS > Drizzle vs. Impala vs. Microsoft SQL Server vs. SiriDB vs. ToroDB

System Properties Comparison Drizzle vs. Impala vs. Microsoft SQL Server vs. SiriDB vs. ToroDB

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.

Analytic DBMS for Hadoop

Microsofts flagship relational DBMS

Open Source Time Series DBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	17.56
Rank	#40	Overall
	#25	Relational DBMS

Score	944.96
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#357	Overall
	#33	Time Series DBMS

Score	0.03
Rank	#342	Overall
	#45	Document stores

Website

www.cloudera.com/products/open-source/apache-hadoop/impala.html

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

siridb.net

www.torodb.com

Technical documentation

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

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

docs.siridb.net

www.torodb.com/stampede/docs

Developer

Drizzle project, originally started by Brian Aker

Cloudera

Microsoft

Cesbit

8Kdata

Initial release

2008

2013

1989

2017

2016

Current release

7.2.4, September 2012

4.0.0, July 2021

SQL Server 2019, November 2019

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

MIT License

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
Windows

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

yes

string, integer, double, boolean, date, object_id

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

JDBC
ODBC

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

HTTP API

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC

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

C
C++
Go
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

yes, but depending on the SQL-Server Edition

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

simple rights management via user accounts

Access rights for users and roles

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd parties

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More resources

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Recent citations in the news

Cloudera Boosts Hadoop App Development On Impala
10 November 2014, InformationWeek

Cloudera's Impala brings Hadoop to SQL and BI
25 October 2012, ZDNet

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Man Busts Out of Google, Rebuilds Top-Secret Query Machine
24 October 2012, WIRED

How to add a data source to Redash
5 April 2022, TechRepublic

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12 July 2022, Redmond Channel Partner

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18 July 2022, Visual Studio Magazine

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