DBMS > Amazon Redshift vs. Ignite vs. Interbase

System Properties Comparison Amazon Redshift vs. Ignite vs. Interbase

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Light-weight proven RDBMS

originally from Borland

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	5.04
Rank	#71	Overall
	#39	Relational DBMS

Website

aws.amazon.com/redshift

ignite.apache.org

www.embarcadero.com/products/interbase

Technical documentation

docs.aws.amazon.com/redshift

apacheignite.readme.io/docs

docs.embarcadero.com/products/interbase

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Embarcadero

Initial release

2012

2015

1984

Current release

Apache Ignite 2.6

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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, .Net

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Android
iOS
Linux
OS X
Windows

Data scheme

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

export as XML data possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

yes

Interbase procedure and trigger language

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

Interbase Change Views

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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