DBMS > Apache Impala vs. Greenplum vs. Oracle Rdb vs. Sadas Engine

System Properties Comparison Apache Impala vs. Greenplum vs. Oracle Rdb vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

impala.apache.org

greenplum.org

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

www.sadasengine.com

Technical documentation

impala.apache.org/impala-docs.html

docs.greenplum.org

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Pivotal Software Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Initial release

2013

2005

1984

2006

Current release

4.1.0, June 2022

7.0.0, September 2023

7.4.1.1, 2021

8.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

free trial version available

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++

Server operating systems

Linux

HP Open VMS

AIX
Linux
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C
Java
Perl
Python
R

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

managed by 'Learn by Usage'

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

Access rights for users, groups and roles according to SQL-standard

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More resources

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