Direct, Native, Out-of-the-Box Business Intelligence On MongoDB

Explore, Query and Report On Live MongoDB Data.
No Mapping. No ETL.

MongoDB Analytics, MongoDB Business Intelligence
The Fastest, Most Agile MongoDB BI Solution
Free Yourself From the Latency, Limitations & Cost That’s Been Holding You Back.


Simply connect to MongoDB and build entire dashboards and interactive reporting in minutes. No mapping. No ETL.


Uncover insights and power your business with agile, ad hoc analytics. 

10X for 1/10

Don’t over invest in more monolithic analytics solutions. With SlamData you get 10x the power at 1/10 the price. 

Scalable, Flexible, Interactive, Embeddable, White Label, Open Source

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Get Your POC Off the Ground Now.

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FAQs on MongoDB
How quickly can I set up SlamData?
SlamData can be downloaded and installed in less than 10 minutes. Simply connect your database and you’ll see your data like never before. From there you can query and visualize your data, as well as publish and share it.
Which versions of MongoDB does SlamData support?
Version 2.6 and newer.
Can SlamData use MongoDB secondary nodes in a replica set?
Yes.  By setting up the connection properly, you can have SlamData perform all of it’s queries against secondaries instead of the primary.
What's the difference between SlamData Community and the Advanced Edition?
SlamData Community Edition has the full analytic capabilities of Advanced. SlamData Advanced comes with multi-tenant security, authentication, authorization and auditing.
Do you support JOINs?
Yes. We leverage the $lookup function if it’s available.
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The Characteristics of NoSQL Analytics Systems

This paper carves out a single concern, by focusing on the system­-level capabilities required to derive maximum analytic value from a generalized model of NoSQL data. This approach leads to eight well­-defined, objective characteristics, which collectively form a precise capabilities­-based definition of a NoSQL analytics system.

  • 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
  • This field is for validation purposes and should be left unchanged.

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