You should now have Kinetica up and running on your own server. In this tutorial, we’ll take you on a quick walkthrough of the product showing you how to query and manage your data. We will also load some sample data that can be used for future exercises.
Kinetica comes with two main visual tools.
- GAdmin – Database Administration GAdmin is the web-based database administration tool for Kinetica. It has all the features of an enterprise-grade database management system.
- Reveal – BI Dashboard Reveal is a BI dashboard for querying and charting data in a usable and interactive way.
GAdmin – Database Administration
GAdmin is the administrative dashboard of the Kinetica database. It is a single stop for the installation, configuration, security, logging, and monitoring of your Kinetica database. GAdmin also provides the means for data ingestion, querying via REST APIs, executing user-defined functions (similar to stored procedures), and monitoring long-running jobs.
GAdmin can be accessed via port 8080.
Load Sample Data
Navigate to the ‘Demo’ section from the left-hand column.
Load the sample data from the NYC Taxi data set. This will load 500K records. You can load more by clicking Load More Data.
The NYC taxi dataset is a public dataset that contains trip information. You can read more about the public data set at “http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml”
In the next tutorial we will show you how to load your own data!
Viewing the Data
Kinetica is a columnar-oriented database that looks and feels much like a relational database. Data is stored in tables with rows and columns.
You’ll be able to view that under the
Data tab. The taxi data has been loaded into the
From this view, you can also create new tables, view the schema, configure the data within, and export data. You can find more information on the capabilities in the GAdmin Documentation.
You can query data in Kinetica through both SQL or the native REST API:
… with SQL
GAdmin comes with a SQL editor which provides a quick way for us to try out some SQL queries.
Try a test query now to check the sample data:
select count(*) from nyctaxi;
We’ll show you more about the capabilities with SQL in the tutorial, Querying with SQL
.. through the API
The native way to query Kinetica is through the REST API. This type of interface is popular with application developers.
The API Query Tool allows you to make calls to the Kinetica REST endpoints. The parameter fields adapt depending on the endpoint. In this case we’ll use the /aggregate/statistics endpoint to count the rows in the database.
We’ll dive deeper with this in the tutorial, Querying the REST API with Python
Kinetica has a comprehensive security model that enterprise users will be familiar with.
- Permissions can be defined on tables, collections.
- Users can be added to the database and assigned these permissions.
- Roles can be created and assigned permissions.
Monitoring Your Server
Kinetica is often used in large, multi-node environments and so GAdmin supports features for monitoring and controlling your clusters.
You can get a feel for the status and resources Kinetica is using with through from the
Reveal: A BI and Analytics Dashboard
Bundled with Kinetica is Reveal, a web-based BI visualization framework for querying and charting of data in an easy, interactive way.
Reveal has a rich set of tools for making dashboards with charts, diagrams, and map visualizations. Multiple users can access these, and dashboards can be shared with others.
Reveal can be accessed from your server at this URL and port:
Default login –
An Example Dashboard
When we loaded the sample data earlier in the chapter, the script also created a sample dashboard for viewing the sample NYC Taxi data.
You can see that dashboard in Reveal from :
Reveal also includes a SQL editor – under SQL Lab – which allows end users to directly interact with their data via SQL statements.
Now that we have loaded the dataset, we can try some queries:
To prevent overloading the browser, select queries are limited to 1000 results.
You could also try something more complex:
SELECT passenger_count, year(pickup_datetime) AS pickup_year, cast (trip_distance as int) AS distance, count(*) AS the_count FROM NYCTaxi GROUP BY 1, 2, 3 ORDER BY 2, 4 desc LIMIT 100
Because Reveal is designed as a BI query tool, only SELECT statements are enabled. It is possible to enable DDL and DML statements within REVEAL if needed.
Did you notice the response time on the right-hand corner in green? It is in milliseconds.
So you just installed the product, loaded 500K of data, and performed some starter queries on the dataset.
In the next tutorial, we’ll show you how to ingest your own data.