DataStax Astra + Knowi = Hybrid Deployment with Unified Analytics

DataStax Astra + Knowi = Hybrid Deployment with Unified Analytics

We recently announced the GA of Astra, DataStax’s cloud-native database-as-a-service (DBaaS) built on Apache Cassandra™, with cloud applications and deployments in mind. Astra allows you to harness all the features and power of Cassandra as-a-service.

While DataStax has led the data evolution beyond relational data, most traditional analytics platforms are stuck in the structured data past. As a result, to perform analytics on DataStax requires you to move data out of Cassandra and back into relational structures either by custom coding data extracts using a SQL driver or through ETL tools.

With the availability of Astra, DataStax has also partnered with Knowi, the company behind the unified analytics platform with a single visualization and data-as-a-service engine to showcase Astra as a newly supported data source. Knowi supports data sources across any infrastructure and can dynamically blend data to create a new, super dataset for analysis.

Through Knowi’s intelligent analytics platform, Astra is available as another data source that can be established alongside your other Cassandra or other database deployments. Whether open-source software (OSS) or DataStax Enterprise (DSE), on-premises, or in a cloud environment, your Cassandra data can be joined across all flavors to perform traditional analytics, build AI & machine learning models or create brilliant visualizations.

For each database source, Knowi provides the query language generator. With CQL, the query generator allows users to select tables, keys, and fields to build CQL queries across all of the Cassandra sources with the ability to join. For the more advanced users who possess stronger query language knowledge, there is also a smart query editor which is a versatile text editor specialized for editing code and comes with a number of language modes and add-ons that implement more advanced editing functionality.

Once the database queries are executed and the data is pulled from the various data sources, Knowi also provides a few ways to analyze this newly blended dataset. The first is with Cloud9QL, a proprietary SQL-like syntax that enables users to aggregate, manipulate, and calculate new data directly without the need for additional data prep tools. Cloud9QL is used to post-process/transform the return data and to complement native queries. Not as a replacement for the underlying query but offers powerful analytics functions on the results returned.

For AI functionality, data can also be aggregated and used in a number of built-in open-source machine learning algorithms. Optionally, you can upload your own proprietary algorithm.

The query functionality doesn’t end there. With natural language processing capabilities in the Knowi platform, even users who have no experience with database query languages can simply ask questions of the dataset. 

Explore our Knowi-powered interactive demo to see just how easy it is to visualize your Cassandra data with Knowi!

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