DBMS > Ignite vs. Infobright vs. Ingres vs. Sadas Engine

System Properties Comparison Ignite vs. Infobright vs. Ingres vs. Sadas Engine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Well established RDBMS

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

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

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

ignite.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.actian.com/databases/ingres

www.sadasengine.com

Technical documentation

apacheignite.readme.io/docs

docs.actian.com/ingres

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

Developer

Apache Software Foundation

Ignite Technologies Inc.; formerly InfoBright Inc.

Actian Corporation

SADAS s.r.l.

Initial release

2015

2005

1974

originally developed at University Berkely in early 1970s

2006

Current release

Apache Ignite 2.6

11.2, May 2022

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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++, Java, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
Linux
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

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
Proprietary protocol

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

Ingres Replicator

none

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

Access rights for users, groups and roles 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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

ArcGIS and Apache Log4j Vulnerabilities
22 May 2023, Esri

provided by Google News

New startup from Postgres creator puts the database at heart of software stack
12 March 2024, TechCrunch

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

Actian Launches Ingres as a Fully-Managed Cloud Service
24 September 2021, Integration Developers

PostgreSQL now top developer choice ahead of MySQL, according to massive new survey • DEVCLASS
13 June 2023, DevClass

Dr. Michael Stonebraker: A Short History of Database Systems
1 February 2019, The New Stack

provided by Google News

Share this page