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.

What Our Customers Are Saying

We use SlamData to build custom reports and have found the tool is exceptionally easy to use and very powerful. We recently needed to engage the support team and we were very pleased with the turn-around time and the quality of support that we received.

Troy Thompson
Director of Software Engineering
Intermap Technologies, Inc.

When our company migrated from SQL database to MongoDB, all our query tools became obsolete. SlamData saved the day! I was able to easily write SQL2 queries. Plus the sharing, charting, and interactive reports were a game changer.

Michael Melmed
VP, Ops and Strategy
US Mobile

Slamdata helped shine the light on how our new product was being used. The support staff was awesome and we saved engineering cycles in building all the analytics in-house. I am using it to change the mindset in the teams and shift the focus from product launches to product landings

Engineering Lead
Cisco Systems

News, Analysis and Blogs

WHITEPAPER

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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SlamData Provides Missing Platform for NoSQL Data Insight

This case study documents the return on investment, performance enhancements, and efficiency gains experienced by US Mobile resulting from its SlamData implementation. 
Download Case Study Now
The study was conducted by Constellation Research and published on June 25, 2017.
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