The Guide To Understanding BI Connectors for NoSQL

Of Course We Can!

The idea of a BI Connector for NoSQL (JSON) databases seems obvious. Popular BI tools like Tableau and PowerBI are widely used by enterprises. These same enterprises are adopting modern databases like MongoDB and Couchbase that store data in very different ways from traditional relational databases (RDBMS) like Oracle and MySQL. So it is very natural for enterprise users to want continue to use the tools they know even when faced with a modern database that stores data in JSON format. Herein lies the challenge!

Oil and Water

NoSQL DB’s are not just simple variations on the RDBMS theme, but are in fact very different. The way they store data is far richer and more complex — it’s anything but relational. For this reason the requirements for a “BI Connector” are very challenging. The simple truth is the user experience with any BI Connector available today has ranged from reasonable to completely unusable, depending on the nature of the data be analyzed (If you are interested in getting down in the technical weeds about why this happens read our whitepaper, The Characteristics of NoSQL Analytics Systems).

The Best BI Connector On the Market

At SlamData we understand some users are determined to find a way forward with their existing tools, and for those users we provide the most functional BI Connector available. It comes as part of SlamData Advanced. Other vendors charge over $25,000 for similar yet inferior technology.

The Best Native NoSQL Analytics Solution On the Market

We also recognized that no BI connector technology can ever fully support the needs of many analysts, for this reason we created the SlamData native solution for NoSQL analytics. It is also 100% open source, and provides complete support for the most complex NoSQL (JSON) data and a powerful UI for creating interactive reports and visualizations that can be easily shared or embedded securely in a SaaS application or reporting dashboard. SlamData is designed to go beyond what a BI Connector can provide from an end user experience. Many of the BIC users run a parallel instance of SlamData.

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The Characteristics of NoSQL Analytics Systems

  • The Nature of NoSQL Data
    • APIs
    • NoSQL Databases
    • Big Data
    • A Generic Data Model for NoSQL
  • Approaches to NoSQL Analytics
    • Coding & ETL
    • Hadoop
    • Real-Time Analytics
    • Relational Model Virtualization
    • First-Class NoSQL Analytics
  • Characteristics of NoSQL Analytics Systems
    • Generic Data Model
    • Isomorphic Data Model
    • Multi-Dimensionality
    • Unified Schema/Data
    • Post-Relational
    • Polymorphic Queries
    • Dynamic Type Discovery & Conversion
    • Structural Patterns
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