DBMS > Amazon Redshift vs. Apache Impala vs. Apache Pinot vs. Informix vs. Oracle

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Apache Pinot vs. Informix vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Widely used RDBMS

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

pinot.apache.org

www.ibm.com/products/informix

www.oracle.com/database

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

docs.pinot.apache.org

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.oracle.com/en/database

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation and contributors

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Oracle

Initial release

2012

2013

2015

1984

1980

Current release

4.1.0, June 2022

1.0.0, September 2023

14.10.FC5, November 2020

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

free developer edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C, C++ and Java

C and C++

Server operating systems

hosted

Linux

All OS with a Java JDK11 or higher

AIX
HP-UX
Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

JDBC

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
Python

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authentication, authorization, and auditing controls

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.