Overview of the SlamData open source project for modern data analytics. SlamData allows users to run ordinary SQL queries on modern NoSQL Data like JSON. Currently we support MongoDB, but plan to support other NoSQL datastores including Cassandra, Hadoop and others. Our project opens up modern NoSQL data to anyone with basic SQL skills.

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Next-Generation Analytics/BI for
Modern Data

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Data is more diverse than ever...
NoSQL, NewSQL, text, logs, JSON, XML. Enterprises have more data
diversity than ever, yet we continue to force the data fit to the analytics
tooling.
SlamData’s philosophy is different: make the analytics fit the data.

3. Relational Data Modern Data
Legacy analytics tooling doesn’t understand modern data!
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The Solution
Powerful, simple, code-free NoSQL analytics on ANY data.
● Native NoSQL analytics, no ETL, no coding
● Expose ubiquitous SQL interface to analysts
● Work with data in place, without need to relocate the data
● Integration across the entire data supply chain
● Open source, low friction, capital efficient market adoption
SlamData is THE foundation for analytics across the
modern data supply chain!

5. Common Ad-hoc
analytics interface
Oracle Postgres SQLSvr MySQL SAP
There is no common analytics interface to
NoSQL data today - until now!
SlamData
MongoDB Hadoop Cassandra Elasticsearch Spark

6. SlamData targets the much larger BI analyst market
Developers
Business
Analysts (BI)
users
SlamData
bridges the
GAP!

7. Why Now?
● Databases do two things:
○ Power applications
○ Support analytics
● NoSQL adoption powering applications is exploding!
○ MongoDB - 7M+ downloads and growing fast
● Analytics is still completely reliant on relational data models,
which are diametrically opposed to the flexibility, agility, and
type of data supported by NoSQL databases
● Today each NoSQL store uses a developer-oriented, one-off
API for querying data. This model cannot scale.
Analytics MUST catch up because the cost and pain of
modern data analytics is too great.
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8. SlamData Strategy
● Make SlamData the business analyst-user friendly STANDARD for ad
hoc analytics on modern data.
● Open Source SlamData engine technology under AGPL 3.0
● Support major NoSQL data sources
○ MongoDB (Oct 2014)
○ Hadoop / Cassandra (Jan 2015)
○ Cloudant / IBM / CouchDB (June 2015)
● Drive developer adoption thru the NoSQL communities/user groups
○ MongoDB, Cassandra, Hadoop, Spark
○ MongoDB World June 2014 official SlamData launch
slamdata.com

9. SlamData Business Model
● SlamData Community Edition - October 2014 (MongoDB)
○ Commercial support available
○ GNU AGPL V3 License
○ OK for internal use / development
○ May include other GPL based applications
○ Obliged to publish modifications and other derivative works
● SlamData Commercial Edition - Q1 2015
○ Commercial end-user licensing
○ Commercial support available
○ Proprietary add-ons to open core
○ Robust Enterprise feature roadmap
● SlamEngine OEM
○ OEM, ISV, SaaS licensing bundle, modify and distribute in
commercial and cloud applications
○ OEM license model for any existing BI solution
○ Integration with any NoSQL DB

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Competitive Landscape
Established RDBMS BI Solutions
● Pentaho, Jaspersoft
● ODBC/JDBC Connectivity - Simba Solutions
ALL are RDBMS-era solutions that rely on complex ETL and
brittle data models
New solutions
● 28 msec JSONiq
○ Proprietary solution, early with little adoption
● JSON Studio
○ Lightweight tools approach, still reliant on an ETL-like
process
○ Proprietary solution, low adoption
● Metanautix
○ Just exited stealth mode, 7M from Sequoia.
○ Market validation
○ Proprietary will hurt adoption in the NoSQL market

11. Competitive Differentiation
Technology is differentiated on dimensions unique to
the challenges of modern data.
● MRAY. A multidimensional extension of relational
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algebra that allows direct analysis of multi-structured,
heterogeneous data.
● Data Discovery. Exploration of the types and
diversity of data stored in NoSQL data stores.
● Data Refinement. First-class, workflow-driven
development reflecting challenges of dealing with
messy, hierarchical, semi-structured data.
Legacy analytics tooling doesn’t have these features
because it doesn’t need to have them.

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Founding Team / Advisors
● Jeff Carr - Co-founder / CEO
○ Experienced entrepreneur and tech executive, multiple exits
○ Strong GTM, sales and team building background
○ Operations and leadership focus
● John De Goes - Co-founder / CTO
○ Veteran startup leader,Techstars Boulder alum,multiple exits
○ Recognized industry expert in Big Data and analytics field
○ Architect and chief designer of SlamData
● Matthew De Goes - Co-founder
○ Veteran startup guy and co-founder
○ Deep experience in digital branding and design
○ Web design, graphics, branding and image management
● Jim Franklin - SlamData Board Member / Investor
○ CEO SendGrid
○ Veteran technology executive, Angel investor, Mentor
○ Former CEO Decisioneering (Acquired by Oracle)