Simba ConnectsDe facto standard connectivity for major Hadoop distributions, leading NoSQL & BI tools

Co-created original ODBC specification with Microsoft

Shipped the first ODBC driver for Hadoop Hive

Compliance with SQL-92 & the latest data connectivity standardsODBC 3.8 & JDBC 4.2

Collaborative Query Execution, fastest performance & advanced deployment options

Automatic schema discovery and re-normalization

Support for engineers by engineers

Widest platform support, including Windows, Mac, Linux, Un*x & iOS

Customers who license & shipSimba's connectivity with their products

A few of our customers who useSimba MongoDB drivers

Customer Feedback

It just works!..Automatic

schema generationworks great...

I don't need to know MongoDB query language!

Great compatibilitywith my <BI tool>...

Really good performanceeven on a laptop

Gets the job done

Simba's Data Connectivity Drivers & SDKs

Thank you.www.simba.com

From Operations to Insights

with MongoDB

Speaker: Evan Castle, Product Manager

→ The Analytical Challenges of MongoDB

→ Example: Customer Use Case for MongoDB

→ Example: Sisense Analytics Driven by MongoDB

Agenda

→ Advantages of Sisense and MongoDB

• Unstructured schemas are poor for analytics

• Difficult to mashup different data sources

• MongoDB is a technical environment, how do

you leverage existing skillsets to analyze

MongoDB

• Not scalable for analytics purposes

The Analytical Challenges of MongoDB

Operational Data vs. Analytical Data

MongoDB Operational Benefits Sisense Analytical Benefits

Dynamic Schema Robust Renormalization

Easy for Programmers Easy for Analysts

Many Attributes Support Many Attributes

Horizontal Scaling Support Big Data

• SQL on NoSQL

• ETL and Easy Visualization

• Mashup Multiple Sources

• Fast Columnar Data Store

• Complex data Immediate query results

• SSL Support

• Intelligent Renormalization

• Performance – aggregation, buffering, batching

Advantages of Sisense on MongoDB

360 Degree View Of Mongodb And All Business Data

• Central location

• Multiple Sources

• Support complex columnar models

Automatic, Visualized Insight for Everyone

• ETL for business

• High performance on large complex data sets

• Visual front end

Sisense Analytics Driven by MongoDB

Customer Use Case for MongoDB

• Reduce time to insight

• Work Flow Automation

• Scale New Services

• Managed by business

Demo

Auto detection

Auto or opportunity to make schema changes

Virtual Tables

Auto or opportunity to make schema changes

Columnar Solution

Sisense offers the ability to analyze data with many columns like MongoDB

Mashup

Drag and Drop mashup

Interactive Dashboards

Anyone can answer complex business questions

Thank you