Direct Business Intelligence on Couchbase

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

Couchbase Analytics, Couchbase Business Intelligence

The Fastest, Most Agile Couchbase BI Solution

Free Yourself From the Latency, Limitations & Cost That’s Been Holding You Back.

Insight

Simply connect to Couchbase and get answers. No mapping. No ETL.y.

Agility

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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FAQs on Couchbase

How long does it take to set up?

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.

What versions of Couchbase does SlamData support?

SlamData currently supports version 4.5.1 exclusively.  Support for 4.6 is coming soon.

What's the difference between the Community and Advanced Editions?

SlamData Community Edition has the full analytic capabilities of Advanced. SlamData Advanced comes with multi-tenant security, authentication, authorization and auditing.

Does SlamData support JOINs on Couchbase?

Yes.  SlamData can leverage the native key join functionality within Couchbase.

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WHITEPAPER

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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