IcCube: Difference between revisions

Edit links
From Wikipedia, the free encyclopedia
Browse history interactively
← Previous editNext edit →
Content deleted Content added
VisualWikitext
m v2.05b - Bot T20 CW#61 - Fix errors for CW project (Reference before punctuation)
(26 intermediate revisions by 14 users not shown)
Line 1: Line 1:
{{Infobox software
{{Infobox software
|developer = icCube software Sarl
| developer = icCube software Sarl
|name = icCube OLAP Server
| name = icCube
|logo = [[File:Iccube-logo.svg|Iccube-logo]]
| logo = [[File:Iccube-logo.svg|Iccube-logo]]
|latest_release_version = 8.4
| latest_release_version = 8.4.10
|latest_release_date = {{release date|2023|02|17}}
| latest_release_date = {{release date|2024|04|10}}
|operating_system = [[Cross-platform]] ([[JVM]])
| operating_system = [[Cross-platform]] ([[JVM]])
|genre = [[Online analytical processing]]
| genre = [[Embedded analytics]]
|website = {{URL |www.iccube.com}}
| website = {{URL |www.iccube.com}}
}}
}}


'''icCube''' is known for its embeddable data analytics and visualization software platform tailored specifically for B2B Software-as-a-Service (SaaS) applications, i.e. [[Embedded analytics]].
'''icCube''' is a company founded in Switzerland that provides [[business intelligence]] (BI) software of the same name. The software can be fully embedded, can be hosted in a managed environment or installed in a customer's machine on premises.


Its customers serve various industries, from finance and healthcare to e-commerce and logistics among many others. The software enables SaaS solutions from multiple sectors to provide data analytics, dashboards and visualization to their respective end-customers (i.e., [[Customer-facing analytics]]).
The BI tool allows end-users to create or edit dashboards themselves and is capable of processing data from multiple sources in real-time. The software makes the dashboards, the dashboard builder, the schema/cube builder and the server monitoring application accessible from a web browser only. No software has to be installed at the device of the end-user.

Next to the browser-based dashboard builder, data can be accessed by running queries directly on the [[OLAP cube]] using MDX, SQL or R.


== History ==
== History ==
icCube sells an [[online analytical processing]] (OLAP) server.


icCube was founded in 2010 by David Alvarez-Debrot and Marc Polizzi, recognizing the need for an analytic server that could be seamlessly integrated into third-party products.
In June 2010 its first public community version (0.9.2) was released. Since then, the company released versions such as:

David and Marc, who had previously worked together in developing a [[financial risk]] product at a software consulting firm, noticed the necessity for a robust, performant and reliable server for analytic calculations. After the roll-out of the financial risk product, they decided to start their own venture.

Initially considering developing an alternative financial risk solution, they later realized the potential in the market for a versatile, cross-solution product focused on analytic modeling and processing that could be easily embedded into any SaaS solution. Many B2B SaaS companies were seeking robust analytics capabilities for their platforms, and the idea behind the company was to be thought-leaders in this space by focusing exclusively on providing an embeddable analytics platform for B2B SaaS solution developers.

The technology is Java-based, ensuring compatibility with most architectures. The in-memory server uses the [[Multidimensional Expressions]] (MDX) query language, which in contrast to other common query languages, is highly optimized for analytics.

Over time, the platform evolved and introduced new features and enhancements to meet the expanding needs of its customers. Noteworthy milestones in the evolution of icCube include the introduction of the Web Reporting server in 2012, the launch of a new reporting system and server calculation engine in 2016, and the release of a new dashboard module based on [[TypeScript]], [[React (software)|React]], [[Redux (JavaScript library)|Redux]], and Material UI (MUI) in 2022.

{| class="wikitable"
{| class="wikitable"
! Date !! Version !! Event
! Date !! Version !! Event
Line 25: Line 31:
| style="width: 100px;" | June 2010 || 0.9.2 || The very first published version (preview) of the in-memory OLAP server; MDX/XMLA support are the primary objectives.
| style="width: 100px;" | June 2010 || 0.9.2 || The very first published version (preview) of the in-memory OLAP server; MDX/XMLA support are the primary objectives.
|-
|-
| November 2010 || 1 || The first features complete (such as MDX and write back) version. A community (free) version.
| November 2010 || 1 || The first features complete. A community (free) version.
|-
|-
| June 2011 || 1.3 || Expanded MDX support and stronger cube modeling features; the first version of the visualization library (GVI).
| June 2011 || 1.3 || Expanded MDX support and stronger cube modeling features; the first version of the visualization library (GVI).
Line 39: Line 45:
| January 2015 || 4.8.2 || Improving the 4.x versions (server features and speed, Web Reporting).
| January 2015 || 4.8.2 || Improving the 4.x versions (server features and speed, Web Reporting).
|-
|-
| May 2015 || 5.1 || Adding [[extract, transform, load]] features.
| May 2015 || 5.1 || Adding [[extract, transform, load|ETL]] features.
|-
|-
| May 2016 || 5.2 || Improving the 5.x versions.
| May 2016 || 5.2 || Improving the 5.x versions.
Line 45: Line 51:
| October 2016 || 6.0 || Brand new reporting and new server calculation engine.
| October 2016 || 6.0 || Brand new reporting and new server calculation engine.
|-
|-
|July 2017 || 6.2 || Added Google Maps layers for GEO widgets, heat maps, etc
|July 2017 || 6.2 || Added Google Maps layers for GEO widgets, heat maps, etc.
|-
|-
|August 2017 || 6.5 || Added dashboard commenting module for collaboration
|August 2017 || 6.5 || Added dashboard commenting module for collaboration.
|-
|-
|April 2018 || 6.6 || Improved ETL + Added dashboard discussions/comments can be filtered by current data filters.
|April 2018 || 6.6 || Improved [[extract, transform, load|ETL]].
|-
|-
|April 2019 || 7.0 || New Server UI / New JSON Rest API
|April 2019 || 7.0 || New Server UI / New JSON Rest API.
|-
|-
|January 2020 || 7.1 || Support for Java 11 and onwards
|January 2020 || 7.1 || Support for Java 11 and onwards.
|-
|-
|March 2023 || 8.0 || New dashboard module (React, Redux, Mui)
|March 2023 || 8.0 || New dashboard module (React, Redux, MUI).
|-
|-
|February 2023 || 8.4 || Java 17, multiprocess support for DOCS, available as a Docker,<ref>{{cite web|url=https://hub.docker.com/u/ic3software|title=Docker}}</ref> libraries in Github<ref>{{cite web|url=https://github.com/ic3-software|title=Github}}</ref>
|February 2023 || 8.4 || Java 17, multiprocess support for DOCS, available as a Docker<ref name="docker">{{cite web|url=https://hub.docker.com/u/ic3software|title=Docker}}</ref> libraries in Github.<ref>{{cite web|url=https://github.com/ic3-software|title=Github|website=[[GitHub]] }}</ref>
|-
|November 2023 || 8.4.6 || Improved performances and print server.
|-
|February 2024 || 8.4.9 || Improved MDX serialization for large results + maintenance release.
|}
|}


== Architecture ==
==Technology==


===Architecture===
⚫
icCube is implemented in the [[Java programming language]] and follows [[J2EE]] standards. For the latter, it embeds both an [[HTTP]] server ([[Jetty (web server)|Jetty]]) and a servlet container to handle all the communication tasks.


⚫
The product is a fully browser-based application, with the server implemented in the [[Java programming language]] following [[J2EE]] standards. For the latter, it embeds both an [[HTTP]] server ([[Jetty (web server)|Jetty]]) and a servlet container to handle all communication tasks. Reporting is developed in [[TypeScript]] / [[React (software)|React]] / [[Redux (JavaScript library)|Redux]].
⚫
Being an in-memory OLAP server, the icCube server does not need to source its data from a RDBMS; any data source that exposes its data in a tabular form can be used; several plugins exists for accessing files, HTTP stream, etc. Accessing datasource that expose JSON objects is also supported (e.g., MongoDB). icCube is then taking care of possibly complex relations (e.g., many-2-many) implied by the JSON structure.


⚫
Being an in-memory server, the server does not need to source its data from a [[Relational database|RDBMS]]; in fact, any data source that exposes its data in a tabular form can be used; several plugins exist for accessing files, HTTP stream, etc. Accessing datasource that expose [[JSON]] objects is also supported (e.g., [[MongoDB]]). The platform then takes care of possibly complex relations (e.g., [[Many-to-many (data model)|Many-to-many]]) implied by the JSON structure.
⚫
Accessing icCube (cube modeling, server monitoring, MDX queries, Web reporting and dashboards) is performed through a Web interface and a JSON Rest API.


⚫
icCube uses [[Multidimensional Expressions]] (MDX) as its query language and several extensions <ref>{{cite web|url=http://cwebbbi.wordpress.com/2010/09/13/iccube/|title=Chris Webb on icCube MDX Declared Functions|date=13 September 2010 }}</ref> to the original language : function declarations,<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=server.mdx.functions|title=MDX Functions Reference (common + extensions)}}</ref> vector (even at measures level), matrix, objects, Java and R integrations.<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=server.mdx_types.types_and_oo_extension|title=icCube extends MDX with OO capabilities}}</ref> icCube patented an MDX debugger.<ref>{{cite web|url=http://www.google.com.ar/patents/US8533218|title=Debugging system for multidimensional database query expressions on a processing server}}</ref>
The icCube OLAP server does not use any caching or pre-aggregation mechanism.


⚫
Accessing the platform (data modeling, server monitoring, MDX queries, dashboards) is performed through a Web interface and a JSON REST API.<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=server.api.index|title=JSON REST API}}</ref>
=== Interfaces ===


===Running icCube===
⚫
icCube uses [[Multidimensional Expressions]] (MDX) as its query language and several extensions <ref>{{cite web|url=http://cwebbbi.wordpress.com/2010/09/13/iccube/|title=Chris Webb on icCube MDX Declared Functions}}</ref> to the original language : function declarations, vector (even at measures level), matrix, objects, Java and R interactions.<ref>{{cite web|url=http://www.iccube.com/newsletter/release-2.5/|title=icCube extends MDX with OO capabilities|access-date=2013-07-18|archive-url=https://archive.today/20130718080759/http://www.iccube.com/newsletter/release-2.5/|archive-date=2013-07-18|url-status=dead}}</ref>
icCube patented an MDX debugger.<ref>{{cite web|url=http://www.google.com.ar/patents/US8533218|title=Debugging system for multidimensional database query expressions on a processing server}}</ref>
icCube supports a standard interface and a proprietary one.
The [[XML for Analysis]] (XMLA) protocol can connect to any compatible reporting tool.


The product can be self deployed on premises and/or in the cloud. It is available as a Windows installer, Linux ZIP file, Mac version and as a Docker container published at Docker Hub.<ref name="docker" />
icCube supports its own proprietary protocol called GVI. [[Http|HTTP]] based, it can be extended.
This protocol uses the Google Visualization wire protocol.<ref>{{cite web|url=https://developers.google.com/chart/interactive/docs/dev/implementing_data_source|title=Implementing the Chart Tools Datasource Protocol (V0.6)}}</ref> Javascript is the primary implementation language and a Java mapping library is also available.


===Key Components===
Since icCube 6.8.6, the icCube server supports a JSON REST API for a programmatic access.

====Server====
* Data modeling – the Builder allows for creating data models (schemas) using a Web based user interface. All the requisite parts of a schema: data sources, dimensions, hierarchies, calculated members, etc. can be defined there.

* API authentication & authorization (SSO) – icCube is hosting a J2EE servlet handler (Jetty) to handle all communications with the server. Authentication is configured via dedicated servlet filters and an internal authentication service. Both can be changed via dedicated Java plugin(s) to meet corporate policies (e.g., SSO). As examples, some customers use Windows SSO, encrypted Web token, etc. Authorization is achieved using roles granting access to resources (i.e., monitoring, schema builders, schema data). Roles can be defined within icCube or generated on-the-fly when users are connecting to the platform using dedicated information (e.g., a list of schemas the users have access to).

* Management API – A REST API (i.e., JSON over HTTP requests) is provided for managing the server and the available schemas.

====Dashboards====

The Dashboards application allows for creating web-based dashboards, based on widgets, gadgets and events:

* Widgets are visual elements such as graphs, charts, maps, filters, etc.
* Gadgets are preconfigured, reusable widgets.
* Events manage interactions between widgets. For example, a filter generates an event that produces an action on a chart. Also, widgets can also contain events and have actions on each other.

===Embedding icCube===

The icCube Dashboards API<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=dashboards.api.Overview|title=icCube Dashboards API}}</ref> allows for:

* developing new themes, widgets (charts, maps, etc.), data transformations, etc
** Plugin dev kit<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=dashboards.api.plugin.Overview|title=Plugin dev kit}}</ref>
** Github: ic3-reporting-api<ref>{{cite web|url=https://github.com/ic3-software/ic3-reporting-api|title=Github: ic3-reporting-api|website=[[GitHub]] }}</ref>
** Source code examples<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=dashboards.api.plugin.Examples|title=Source code examples}}</ref>
* embedding icCube Dashboards into a Web application
**Embedded API<ref>{{cite web|url=https://doc.iccube.com/?ic3topic=dashboards.api.embed.Overview|title=Embedded API}}</ref>
**Github: ic3-reporting-api-embedded<ref>{{cite web|url=https://github.com/ic3-software/ic3-reporting-api-embedded|title=Github: ic3-reporting-api-embedded|website=[[GitHub]] }}</ref>

== AnalyticsOps ==

With icCube v8.4.10, a new Github public project has been published : ic3-analytics-ops.<ref>{{cite web|url=https://github.com/ic3-software/ic3-analytics-ops|title=Github: ic3-analytics-ops|website=[[GitHub]] }}</ref> This projects allows for (automated) testing the Analytics and Dashboards built with icCube.


== See also ==
== See also ==
*[[Embedded analytics]]
⚫
* [[Comparison of OLAP servers]]
*[[Customer-facing analytics]]
* [[Business intelligence]]
⚫
*[[Comparison of OLAP servers]]


== References ==
== References ==
Line 91: Line 129:


[[Category:Online analytical processing]]
[[Category:Online analytical processing]]
⚫
[[Category:Business intelligence companies]]
⚫
[[Category:Business intelligence software]]
[[Category:Data analysis software]]
[[Category:Data analysis software]]
[[Category:Reporting software]]
[[Category:Reporting software]]
⚫
[[Category:Data visualization software]]
[[Category:Data companies]]
⚫
[[Category:Business software companies]]

==External links==
* {{Official website|https://www.iccube.com/}}

Revision as of 07:11, 19 April 2024

icCube
Developer(s)icCube software Sarl
Stable release
8.4.10 / April 10, 2024 (2024-04-10)
Operating systemCross-platform (JVM)
TypeEmbedded analytics
Websitewww.iccube.com

icCube is known for its embeddable data analytics and visualization software platform tailored specifically for B2B Software-as-a-Service (SaaS) applications, i.e. Embedded analytics.

Its customers serve various industries, from finance and healthcare to e-commerce and logistics among many others. The software enables SaaS solutions from multiple sectors to provide data analytics, dashboards and visualization to their respective end-customers (i.e., Customer-facing analytics).

History

icCube was founded in 2010 by David Alvarez-Debrot and Marc Polizzi, recognizing the need for an analytic server that could be seamlessly integrated into third-party products.

David and Marc, who had previously worked together in developing a financial risk product at a software consulting firm, noticed the necessity for a robust, performant and reliable server for analytic calculations. After the roll-out of the financial risk product, they decided to start their own venture.

Initially considering developing an alternative financial risk solution, they later realized the potential in the market for a versatile, cross-solution product focused on analytic modeling and processing that could be easily embedded into any SaaS solution. Many B2B SaaS companies were seeking robust analytics capabilities for their platforms, and the idea behind the company was to be thought-leaders in this space by focusing exclusively on providing an embeddable analytics platform for B2B SaaS solution developers.

The technology is Java-based, ensuring compatibility with most architectures. The in-memory server uses the Multidimensional Expressions (MDX) query language, which in contrast to other common query languages, is highly optimized for analytics.

Over time, the platform evolved and introduced new features and enhancements to meet the expanding needs of its customers. Noteworthy milestones in the evolution of icCube include the introduction of the Web Reporting server in 2012, the launch of a new reporting system and server calculation engine in 2016, and the release of a new dashboard module based on TypeScript, React, Redux, and Material UI (MUI) in 2022.

Date Version Event
June 2010 0.9.2 The very first published version (preview) of the in-memory OLAP server; MDX/XMLA support are the primary objectives.
November 2010 1 The first features complete. A community (free) version.
June 2011 1.3 Expanded MDX support and stronger cube modeling features; the first version of the visualization library (GVI).
October 2011 2 First version advertised for business use (vs. community).
April 2012 2.5 First version featuring the Web Reporting server.
January 2013 3 Better performance and more features.
June 2013 4 A second generation calculation engine.
January 2015 4.8.2 Improving the 4.x versions (server features and speed, Web Reporting).
May 2015 5.1 Adding ETL features.
May 2016 5.2 Improving the 5.x versions.
October 2016 6.0 Brand new reporting and new server calculation engine.
July 2017 6.2 Added Google Maps layers for GEO widgets, heat maps, etc.
August 2017 6.5 Added dashboard commenting module for collaboration.
April 2018 6.6 Improved ETL.
April 2019 7.0 New Server UI / New JSON Rest API.
January 2020 7.1 Support for Java 11 and onwards.
March 2023 8.0 New dashboard module (React, Redux, MUI).
February 2023 8.4 Java 17, multiprocess support for DOCS, available as a Docker[1] libraries in Github.[2]
November 2023 8.4.6 Improved performances and print server.
February 2024 8.4.9 Improved MDX serialization for large results + maintenance release.

Technology

Architecture

The product is a fully browser-based application, with the server implemented in the Java programming language following J2EE standards. For the latter, it embeds both an HTTP server (Jetty) and a servlet container to handle all communication tasks. Reporting is developed in TypeScript / React / Redux.

Being an in-memory server, the server does not need to source its data from a RDBMS; in fact, any data source that exposes its data in a tabular form can be used; several plugins exist for accessing files, HTTP stream, etc. Accessing datasource that expose JSON objects is also supported (e.g., MongoDB). The platform then takes care of possibly complex relations (e.g., Many-to-many) implied by the JSON structure.

icCube uses Multidimensional Expressions (MDX) as its query language and several extensions [3] to the original language : function declarations,[4] vector (even at measures level), matrix, objects, Java and R integrations.[5] icCube patented an MDX debugger.[6]

Accessing the platform (data modeling, server monitoring, MDX queries, dashboards) is performed through a Web interface and a JSON REST API.[7]

Running icCube

The product can be self deployed on premises and/or in the cloud. It is available as a Windows installer, Linux ZIP file, Mac version and as a Docker container published at Docker Hub.[1]

Key Components

Server

  • Data modeling – the Builder allows for creating data models (schemas) using a Web based user interface. All the requisite parts of a schema: data sources, dimensions, hierarchies, calculated members, etc. can be defined there.
  • API authentication & authorization (SSO) – icCube is hosting a J2EE servlet handler (Jetty) to handle all communications with the server. Authentication is configured via dedicated servlet filters and an internal authentication service. Both can be changed via dedicated Java plugin(s) to meet corporate policies (e.g., SSO). As examples, some customers use Windows SSO, encrypted Web token, etc. Authorization is achieved using roles granting access to resources (i.e., monitoring, schema builders, schema data). Roles can be defined within icCube or generated on-the-fly when users are connecting to the platform using dedicated information (e.g., a list of schemas the users have access to).
  • Management API – A REST API (i.e., JSON over HTTP requests) is provided for managing the server and the available schemas.

Dashboards

The Dashboards application allows for creating web-based dashboards, based on widgets, gadgets and events:

  • Widgets are visual elements such as graphs, charts, maps, filters, etc.
  • Gadgets are preconfigured, reusable widgets.
  • Events manage interactions between widgets. For example, a filter generates an event that produces an action on a chart. Also, widgets can also contain events and have actions on each other.

Embedding icCube

The icCube Dashboards API[8] allows for:

  • developing new themes, widgets (charts, maps, etc.), data transformations, etc
    • Plugin dev kit[9]
    • Github: ic3-reporting-api[10]
    • Source code examples[11]
  • embedding icCube Dashboards into a Web application
    • Embedded API[12]
    • Github: ic3-reporting-api-embedded[13]

AnalyticsOps

With icCube v8.4.10, a new Github public project has been published : ic3-analytics-ops.[14] This projects allows for (automated) testing the Analytics and Dashboards built with icCube.

See also

References

  1. ^ a b "Docker".
  2. ^ "Github". GitHub.
  3. ^ "Chris Webb on icCube MDX Declared Functions". 13 September 2010.
  4. ^ "MDX Functions Reference (common + extensions)".
  5. ^ "icCube extends MDX with OO capabilities".
  6. ^ "Debugging system for multidimensional database query expressions on a processing server".
  7. ^ "JSON REST API".
  8. ^ "icCube Dashboards API".
  9. ^ "Plugin dev kit".
  10. ^ "Github: ic3-reporting-api". GitHub.
  11. ^ "Source code examples".
  12. ^ "Embedded API".
  13. ^ "Github: ic3-reporting-api-embedded". GitHub.
  14. ^ "Github: ic3-analytics-ops". GitHub.

External links

Retrieved from "https://en.wikipedia.org/w/index.php?title=IcCube&oldid=1219688782"