MammothDB is the first inexpensive enterprise analytics database, offered in the cloud or on-premises.
It's pointless to have big, or even medium sized data, if you don't have the ability to easily use and understand that data. We're making enterprise analytics accessible to every company in the world, particularly the under-served 88% of global companies that don't have enterprise analytics/business intelligence today.
2. inexpensive analytics
MammothDB replaces Oracle
and Teradata for analytics solutions
starting now,
there’s no reason to use
expensive databases for
enterprise analytics
3. 3
team: analytics experts
alex aldev
angel mitev
co-founder: COO & BI
steve keil
co-founder: CEO & sales
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• architect of DHL’s global Business Intelligence solution,
which is still in use;
• DWH and analytics guru (including ETL, DB, Cubes,
Reporting) for global 2000 firms over 10 years;
• previous companies include DHL, SBB (Swiss Rail), Cabletel
• 4x entrepreneur, last exit – the sale of Sciant to VMware
(VMW) in 2008;
12+ years sales & marketing industry experience;
• speaker and promoter: featured on TED.com:
http://bit.ly/V40aAW
• 3x entrepreneur (co-founder of Sciant & Scaletools),
including exit to VMW;
• BI subject matter expert, over 12 years experience in the
field;
• program management for BI projects at SBB, Siemens, and
DHL
co-founder: CTO & BI
4. 4
the problems we solve
WHAT’S THE POINT OF STORING BIG DATA…
IF WE CAN’T AFFORD TO EASILY USE IT ?!?
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DWH & analytics solutions are ridiculously expensive,
especially when you have big or enterprise data
modern NoSQL solutions are both slow & difficult for the
business person to use. Oh, did we mention…
they’re also expensive?
this means most companies simply
can’t afford to gain insight from their data!
5. the mammothdb solution
GET:
1. LIGHTNING FAST QUERIES – 1-2 seconds fast
2. SQL NATIVE – use the reporting tool you want
3. FLEXIBILITY – on-premises or cloud solutions
4. INEXPENSIVE ANALYTICS – DWH for 10x less
a. LINEAR COST SCALABLE – big data, less price
5
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make it fast & easy to use, with MammothDB; including our
interactive engine & query re-writer (SQL native & accepts
standard schemas)
start with hadoop, the leading platform for big data, and an
amazing parallel processing engine - use only parts of it
6. 6
value: business users ♥ us
MAMMOTHDB DELIVERS INTERACTIVE
QUERY TIMES (1-2 seconds)
mammothdb enables users to start analyzing quickly by:
• using standard data schemas, and
• industry standard reporting tools they already have and use!
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business users definitely don’t want to learn SQL-like
programming languages. We are SQL-native!
business users don’t wait hours, or even minutes, to
get reports: they want them fast!
7. 7
MammothDB
value: lowering total cost
VALUE PREVENTION VALUE CREATION
VS.
NEW WAY
+
=
+
=
OLD WAY
inexpensive
Hadoop nodes
expensive
servers &
backup hardware
expensive
database
expensive – $500K & more, just for
software and hardware
inexpensive – analytics for 10x less,
providing insights, not expenses
inexpensive
database
8. beta version completed Q2 2013, and
now production version released!
milestones & traction
8
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Global Logistics Company our first paying customer
Top-3 transportation company globally; providing positive
feedback & extending our license agreement through 2014
signed Global Media Company – Our next paid customer!
Top-3 global media company; new agreement to analyze social
media data across multiple channels.
channel partners – signing our first three channel partners
EU innovation award winner
MammothDB chosen among the top innovative
startup technology companies in Europe, and
awarded a €175,000 innovation grant
9. (IDC) the business analytics software market grew by 14% in 2011,
and will reach $50.7 billion in 2016, all driven by the focus on
complicated and big data. data is getting bigger, and harder!
9
MARKET SIZE
ADOPTION RATE
market size & focus
DISRUPTIVE VISION
the enterprise analytics adoption rate is as low as 10% of the
market, meaning high costs are a massive barrier to entry!
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we believe that to disrupt an existing market, a 10x or greater cost
savings is needed. our vision is to tackle the 90% existing market, and
enable the entire world to gain wisdom from their data.
We focus on the under-served medium to large sized companies
(100M+ revenue) that can’t afford today’s enterprise analytics solutions.
10. • HADAPT (~17M)
• IMPALA/CLOUDERA (~141M)
• PLATFORA (~27M)
• JEHTRODB (~4.5M)
• SPLICE MACHINE (~19M)
competitor snapshot
10
ORACLE-EXADATA
MICROSOFT-PDW
TERADATA-ASTERDATA
EMC-GREENPLUM
IBM- NETEZZA
HP-VERTICA
ESTABLISHED PLAYERS SOME NEW STARTUPS
we view the old traditional plays as
our real competition…
there’s a lot of new “big data”
companies, but most of them
aren’t designed for analytics – they
focus on “big data,” & aren’t
interactive, or effective, for the real
business world. they are also terribly
capital inefficient.
11. 11
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5 reasons why we’ll win
our technology approach is the future of analytics: (next slide please)/05
we’re focusing on real business problems,
• where customers and prospects experience a lot of pain, not on the hype
of “big data.” business users are the target, who have specific problems
over mid sized and tough data. that’s the real pain, and the real market.
capital efficient operations and development,
• we do a lot with a little, reaching beta while being self-funded, and our
production ready system is on par with our competitors!
we’re disrupting the existing business analytics market,
• rather than creating a new, limited market of “big data” companies. few
companies really have very big data: most have “tough” data to analyze,
of less than 1 TB. we focus on real problems, not the “big data” tiny market.
SaaS and On Premises at a low cost price-point:
• we’re the only viable low cost enterprise analytics alternative on the
market – all our competitors are striking price points similar to enterprise
versions of Oracle, Teradata, or Vertica implementations. why would a
company pay the same money for an untested new kid on the block?
12. 12
/A
/B
MammothDB:
pre-structured data stored and
processed by optimized data
engines, on each Hadoop node!
VS.
= wasteful use of CPU/network,
and inefficient for analytics
= amazing efficiency and speed
MDB: future of data analytics
SQL-over hadoop competitors:
unstructured data stored on the file
system, processed at query time:
13. warning: the next slide
is geeky and full of text,
but does explain the
evolution (and devolution) of
analytics, and how we feel
MammothDB is different
14. evolution of data analytics
MAINFRAME SQL
DATA
WAREHOUSING
HADOOP
SQL-OVER
HADOOP
MAMMOTHDB
• one big server
• transactions &
analytics on
the same box
• only
programmers
can run
reports
• batch
processing,
very slow
• one big
server
• transactions
&
analytics on
the same box
• batch
processing,
very slow
• finally, an
easier
interface for
writing
queries (SQL)!
• two servers!
• transactions &
analytics on
different boxes!
• interactive
processing!
• an easier
interface for
writing queries
(SQL)!
• horribly
expensive
• many small
servers
(clustering)
• transactions &
analytics on
the same box
• only
programmers
can run
reports
• batch
processing,
very slow
• many small
servers
(clustering)
• transactions &
analytics on
the same box
• clumsy
processing,
fairly slow
• finally, an
easier
interface for
writing queries
(SQL)!
• many small
servers
(clustering)
• transactions &
analytics on
different boxes!
• interactive
processing!
• an easier
interface for
writing queries
(SQL)!
• awesomely
inexpensive
15. ON PREMESISSaaS: ENTERPRISESaaS: SMB
monthly subscription
• smaller data sets
• prototyping
• quick solutions
• freemium model
• annual contracts
• ad-hoc & hourly
monthly subscription
• larger data sets
• custom solutions
• enterprise integrations
• paid, w/support
license fees & free
• traditional enterprise
• big data requirements
• on-site security policies
• complex integration needs
revenue models
PAID SUPPORT
• consulting
• customization
• “health” checks
• implementations
PROFESSIONAL SERVICES
• one & two day
trainings, plus
• half day workshops
TRAINING
+ +
16. 16
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go-to-market approach
channels & partnerships – creating partnerships with consulting
companies, integrators, hardware firms, and software
companies (e.g. reporting and ETL tools)in order to really scale
freemium – fulfilling our promise of low-cost, helping customers start
free, then grow smoothly into our subscription or on-premises plans
direct sales – Our first customers are made through direct sales
in our network. we’re expanding into new areas(e.g. telecoms
& banking), and our pipeline is growing
Disrupting the sales cycle :
Anyone who tells you that enterprise analytics has a “short” sales cycle is
flat-out lying. It’s never been short, because prices are high, and therefore
risk is high. Until now – we’ve seen a 3x reduction in sales cycle time!
17. data size + complexity
cost
millions
cheap
small / easy medium (100’s GB) big / complex (TB’s) huge
analytics DB position: today
18. analytics DB position: tomorrow
data size + complexity
cost
millions
cheap
small / easy medium (100’s GB) big / complex (TB’s) huge
19. summary: key disruptions
native SQL-compliant database:
• providing seamless integration with existing reporting tools & data
schemas. this is what the market wants: business users like SQL,
and they like one of the already existing 1,000+ reporting tools.
19
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MammothDB is fast & scalable:
• sub-second second query responses over tough data.
inexpensive analytics means more companies gain insight:
• we’re the low cost airline carrier. we get you there, cheaper.
maybe not as glamorous as a premium carrier, but now it means
more people can fly.
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MammothDB is disrupting the real/existing market:
• we focus on the *actual* market – enterprise data! the dirty
secret out there is that most people struggle with 100’s of GB of
enterprise data – and we’ll help them do that!