FAQs

General

What are Kibi use cases?

Examples of use cases that Kibi addresses:

  • User and system behavior: From a simple log, kibi addresses which user or system did this and that and that_ (and show the analytics) (high performance drill down and self-join on the log index).
  • Security and IP Intelligence: Keep a list of threats (MD5s IPs) in independent indexes;  at the press of button users may zoom in on the logs from compromised machines.
  • Market Intelligence: Maintain an updated list of news about companies, and zoom in on the news involving companies which have the needed properties.
  • Business Intelligence Meets Enterprise Search: Kibi can provide functions commonly available in BI software along with added real time integration via streaming social media, news feeds, and analysts’ reports. What are the most purchased products by customers that, during any email or support interactions have mentioned the name of a competitor? How has this been evolving over time?
  • Life Science: Explore using facets, drilldowns, targets/assays/chemical structures related to published papers mentioning certain keywords
  • National Defense, Antiterrorism: Zoom in on suspects from content of their communications, which extends your search by filters created by querying an external high performance graph store.
  • Internet of Things, Sensors Data: Drill down on sensor logs detecting certain events, pivot to the “sensor index” view and see their common properties, pivot on the properties of the locations where they’re installed. Real time.
  • Credit Rating, Compliance, FinancialFilter and receive analytic scrossing news, tweets, reports, emails with financial data, real time transactions, people, and products
  • Technical/Legal Publishing: Documents and Legislations referred to in cases which were managed by certain people and had specific outcomes.
  • Law Enforcements: Violations <→ Offenders <→ Vehicle Database <→ Camera and Sensor Readings
  • Local Authority Planning: Relate building permission document content, to records about the architects, owners, and nearby buildings

What are Kibi/Siren Join and how do they compare with Elasticsearch/Kibana?

What is Kibi/Siren Join and how do they compare with Elasticsearch/Kibana?

Siren Join is the Siren Solutions  plugin for Elasticsearch which allows high efficiency joins across data in elasticsearch  In practice, it extends Elasticsearch with capabilities to handle interconnected networks of complexly structured documents.

Kibi is a “friendly fork” of Kibana, born from our excitement for Kibana and our desire to deliver the power and flexibility of Kibana and Elasticsearch to use cases involving complex/interconnected knowledge. To work its magic, Kibi makes strong use of the Siren Join Plugins capabilities.

Siren Solutions is committed to track the latest developments of Kibana so to offer the very latest Kibana/Elasticsearch features enhanced with the Siren Plugin/Kibi capabilities for Data Intelligence.

Key Features Added to Kibana 4.4

  • Tabbed UI, with Tab Groups with info on the tab labels
  • Joins (Filters) across Elasticsearch indexes – in memory and via high performance Elasticsearch plugin.
  • Joins (Filters and Aggregators) accessing Relational Databases, NoSQL and Rest API
  • Graphic cross index schema configuration – visual “cross index” filtering with the “relational panel”
  • Clickable “entities”, can trigger updates on filters and results. Click responsive templated visualizations.
  • Wordcloud component, Timeline component (Multi Index Plugins), Radar Chart plugins and others

Other features available upon request :

  • Complex Event Processing – CEP, capabilities
  • Graph Analytics capability

Does Kibi remove anything from Kibana? Is there any reason to use Kibana over Kibi?

Kibi removes none of the features of Kibana, so we think of it as a no brainer replacement.

Be aware, however, that Kibi tabbed interface cannot be disabled at the moment so you might want to consider this.

Will Kibi follow Kibana? When is compatibility with Elasticsearch X.X.X coming?

Kibi is a “Kept in Sync” Fork: we tracks,  the latest Kibana deployment and we’re committed to do so in the future, so you get all the good stuff in there, worry not.

Unlike Kibana however Kibi versions are not “locked in” to a specific Elasticsearch version. In other words. Kibi 4.4.1 – for example, will work also on later Elasticsearch (at the time of this writing Elasticsearch 2.3.3). So, given a few days after each release, you can expect Kibi to be able to run always on the latest available Elasticsearch.

Kibi Licence

Kibi is distributed as Apache 2.0. Kibi uses the SIREn Join plugin which is distributed as Affero GPL.

In legal terms, the combination of Siren join and Kibi is very similar to that of MongoDB (AGPL) with its Drivers (Apache). (people use and may extend the drivers, so they wont be affected by the AGPL in dowstream applications)

Here is how we mean it in practice and ask you to respect this:

  • You Can use Kibi freely for inside your organization for any purpose without limitations.
  • You Can take pieces of Kibi code and commit them elsewhere (E.g. contribute to Kibana :) )

However notice that if you intend to

  • Extend Kibi or write plugins for it,  that are not simply Kibana plugins and are not themselves distributed as AGPL
  • Embed Kibi into your solution for your customers (OEM), distribute Kibi along with other software, that is not AGPL

you should then request a Kibi EE licence to do so by contacting us.

Data Loading

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Does Kibi require all the data to be loaded in Elasticsearch?

No. Kibi supports for External Data sources such as typically SQL and generic REST sources.

Kibi can query these sources on the fly at user navigation to create special filters or special “external query” aggregators (e.g. to use in visualizations).

Generally speaking, you have to load all the data that will intend perform search and complex analytics must be loaded. But you do not need to materialize or import auxiliary data e.g. that is only used for visualizations or to create filters.

Should data be loaded necessarely with Logstash?

Not necessarily. Logstash (which we use in our fully worked out example) is a very handy tool for loading data into Elasticsearch/Siren 2.0 – thus in Kibi, but it is not the only choice.

ETL can be performed in many ways, e.g. by custom scripts or by using ETL/data workflow/messaging tools found such as Talend, CloverETL, Kafka etc.

Kibi Enterprise Edition

What is Kibi Enterprise Edition?

Kibi Enterprise Edition is the commercial offering of Kibi. Its flexibly licenced and has many additional features please see here

Technical Bits

Accessing a SQL database through JDBC

If you want to access a SQL database through a JDBC driver, you need to load JDBC bindings before starting Kibi.

Edit “config/kibi.yml” and add the following line:

Recompiling JDBC module manually

In order to connect to SQL database through JDBC, native JAVA bindings are needed. Although Kibi ships native JAVA bindings for MacOS, Linux, and Windows, it may happen that the version of some native library dependency is too old/recent. To go around this, you can compile the bindings on your machine:

File Permissions

If you have issues starting or accessing Kibi, make sure that you have read access to the following files:

  • /opt/kibi/optimize/
  • /opt/kibi/node/bin/
  • /opt/kibi/bin/

This assumes that you unziped the Kibi distribution to “/opt/kibi“.

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