DBMS > Apache Impala vs. IRONdb vs. Microsoft SQL Server vs. Oracle Rdb vs. SAP Advantage Database Server

System Properties Comparison Apache Impala vs. IRONdb vs. Microsoft SQL Server vs. Oracle Rdb vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Microsofts flagship relational DBMS

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

impala.apache.org

www.circonus.com/solutions/time-series-database/

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

www.oracle.com/database/technologies/related/rdb.html

www.sap.com/products/advantage-database-server.html

Technical documentation

impala.apache.org/impala-docs.html

docs.circonus.com/irondb/category/getting-started

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Circonus LLC.

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sybase, SAP

Initial release

2013

2017

1989

1984

1993

Current release

4.1.0, June 2022

V0.10.20, January 2018

SQL Server 2022, November 2022

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C and C++

C++

Server operating systems

Linux

Linux
Windows

HP Open VMS

Linux
Windows

Data scheme

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL-like DML and DDL statements

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
ODBC

HTTP API

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in Lua

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

Automatic, metric affinity per node

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

configurable replication factor, datacenter aware

yes, but depending on the SQL-Server Edition

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
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 per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

caching of (temporary) tables can be configured

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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