Full-Blown BI On Hadoop.

Query, Chart & Build Dashboards On Live Data.

Hadoop Analytics, Hadoop Business Intelligence, Hadoop BI

Enterprise Features That Deliver Immediate ROI


Connect and Go

SlamData delivers Hadoop analytics within a few minutes and requires no software developer. This isn’t a few nifty charts – it’s enterprise grade and 100% customizable.


Skip ETL = Save Big

Think you have to move data to analyze it?  With SlamData, you can get the analytics and reporting you need while leaving data right where it is. 


Stick With SQL

SQL is the language your team already knows. Don’t learn new query languages for every new data store.


Embed Analytics Anywhere

In 15 minutes you can create beautiful, secure and scalabable dashboards that run on live Hadoop data. Then embed them anywhere you want. 

See Out-of-the-Box Analytics for Hadoop

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Turnkey Solutions For Every Industry. Results Day 1.

SaaS Analytics

With SlamData you can see Immediately what your customers are doing — evaluate by cohort, look for outliers, track them over time. You can even use SlamData to create a dashboard or to deliver data BACK to your end users. SlamData Advanced offers Authentication, auditing and multi-tenant security.

Healthcare Analytics

With SlamData you can find patients, review their attributes, group patients, create dynamic reports and more. SlamData Advanced provide all the security features needed to ensure regulatory compliance.

IoT Analytics

SlamData lets you see your data as it’s created. You can build dynamic and interactive charts and dashboards so you can visualize what’s going on right now with 10, 10,000 or 10,000,000 devices.

Security Analytics

SlamData gives you insight into your data immediately. And as soon as you can define what the most important “view” of that data is for your clients, hit “publish” and share it with them. In fact, use our Multi-tenant feature to build dashboards for all of your clients.

It's incredible technology. At first we used it to save time but now we're using it to create opportunties we never thougt we'd have.

Jay - Software Developer

News, Blog and Updates

SlamData Secures $6.7MM Series A to Support Modern Data in the Enterprise

Boulder, Colo., February 23, 2017 – SlamData Inc., the leading open source analytics company for modern unstructured data today announced that it has raised a $6.7M Series A funding round, led by Shasta Ventures. The investment will drive further development of the firm’s breakthrough analytics solution: a single application for natively exploring, visualizing and embedding analytics against unstructured data sources including NoSQL, Hadoop, and cloud API’s.

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Getting Started With SlamData – Part 1

Welcome to the SlamData getting started video. Let’s jump right in. By default, SlamData runs on port 20223. You can change the port it runs on by modifying the quasar-config.json file. By default, this file is located in the following directories on Windows, Mac and Linux.

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Whitepaper: The Characteristics of NoSQL Analytics Systems

by John De Goes, CTO and Co-Founder of SlamData


Semi­structured data, called NoSQL data in this paper, is growing at an unprecedented rate.  This growth is fueled, in part, by the proliferation of web and mobile applications, APIs, event­-oriented data, sensor data, machine learning, and the Internet of Things, all of which are disproportionately powered by NoSQL technologies and data models.

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.

These capabilities are inextricably motivated by use cases, but other considerations are explicitly ignored. They are ignored not because they are unimportant (quite the contrary), but because they are orthogonal to the raw capabilities a system must possess to be capable of deriving analytic value from NoSQL data.

Table of Contents

  • Overview
  • 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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