DBMS > Apache Impala vs. Microsoft SQL Server vs. RRDtool vs. SAP IQ

System Properties Comparison Apache Impala vs. Microsoft SQL Server vs. RRDtool vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Microsofts flagship relational DBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

impala.apache.org

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

oss.oetiker.ch/rrdtool

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

impala.apache.org/impala-docs.html

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

oss.oetiker.ch/rrdtool/doc

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

Tobias Oetiker

SAP, formerly Sybase

Initial release

2013

1989

1999

1994

Current release

4.1.0, June 2022

SQL Server 2022, November 2022

1.8.0, 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

GPL V2 and FLOSS

commercial

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++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

Linux
Windows

HP-UX
Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

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

in-process shared library
Pipes

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

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

yes

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 disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, but depending on the SQL-Server Edition

none

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

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

by using the rrdcached daemon

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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