SlamData 4.1 Includes New Charts, Updated Connectors for…

Chris Dima
Chris Dima


SlamData just released its first update of 2017, SlamData 4.1.1. It delivers a number of new UI enhancements, performance improvements, new charts, as well as commercial releases for the Couchbase, MarkLogic and Spark/Hadoop connectors.

SlamData 4.1 delivers improved performance and polish over 4.0, and raises the bar on what you can do visually without using SQL

“SlamData 4.1 delivers improved performance and polish over 4.0, and raises the bar on what you can do visually without using SQL,’ said John De Goes, CTO and Co-Founder. “In addition, our support for MarkLogic, Couchbase, and Hadoop/Spark has been through two months of beta testing, with many performance and quality improvements.”

5 New Charts for Visualizing Your Data and Creating Rich Dashboards

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No ETL. No Mapping. No Stale Extracts.

Data Sources

  • Completion of Couchbase connector; now supports key joins.
  • Completion of MarkLogic connector; now supports both XML and JSON.
  • Completion of Spark/Hadoop connector.

New Charts

  • Sankey
  • Boxplot
  • Punchard
  • Candlestick
  • Parallel

User Interface

  • Now any card in a deck can now be mirrored; Previously only the last card in a deck could be mirrored.
  • Forms can now be built using cards rather than Markdown. This makes adding menus and inputs to dashboards easier.


  • Improved caching.
  • Authentication is no longer attempted if a permission token is present. This increases the loading speed of decks with permission tokens by unauthenticated consumers.
  • The Embed Deck HTML has been improved. Embedded decks now work better out the box and also provide deck URLs which allows for simpler and more powerful integration with other applications.
  • Decks are now saved in a single workspace file which reduces the number of requests.
  • The open card now includes search making selecting a file from a long listing much easier.

News, Analysis and Blogs

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


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

“The ROI has been in saving my time building, refreshing and tweaking reports and saving the time of engineers, who would otherwise have to build custom reports for our analytics portal."

- Michael Melmed, US Mobile
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The study was conducted by Constellation Research.
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