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==History==
==History==
Todd Mostak and Thomas Graham founded HEAVY.AI, then named MapD, in 2013. Since their foundation, the company has focused on providing its services to a variety of markets, including government, public and private companies.<ref>{{cite web|last1=Wadhwa|first1=Tina|title=I listened to 82 finance startup pitches — here's what I learned about where Wall Street is heading|url=http://uk.businessinsider.com/financial-technology-pitches-finovate-future-of-wall-street-2016-9?r=US&IR=T|publisher=[[Business Insider]]|date=September 22, 2016}}</ref><ref>{{cite web|last1=McKenna|first1=Brian|title=Silicon Valley startups home in on pressing value from data|url=https://www.computerweekly.com/feature/Silicon-Valley-startups-home-in-on-pressing-value-from-data|publisher=[[Computer Weekly]]}}</ref>
Todd Mostak and Thomas Graham founded HEAVY.AI, then named MapD, in 2013. Since their foundation, the company has focused on providing its services to a variety of markets, including government, public and private companies.<ref>{{cite web|last1=Wadhwa|first1=Tina|title=I listened to 82 finance startup pitches — here's what I learned about where Wall Street is heading|url=https://www.businessinsider.com/financial-technology-pitches-finovate-future-of-wall-street-2016-9?r=US&IR=T|publisher=[[Business Insider]]|date=September 22, 2016}}</ref><ref>{{cite web|last1=McKenna|first1=Brian|title=Silicon Valley startups home in on pressing value from data|url=https://www.computerweekly.com/feature/Silicon-Valley-startups-home-in-on-pressing-value-from-data|publisher=[[Computer Weekly]]}}</ref>


HEAVY.AI's main offering is the Core database system, which was developed shortly after the company was founded.<ref>{{cite web|last1=Barinka|first1=Alex|title=Database Startup MapD Raises $10 Million From Google, Nvidia|url=https://www.bloomberg.com/news/articles/2016-03-30/database-startup-mapd-raises-10-million-from-google-nvidia|publisher=[[Bloomberg L.P.|Bloomberg]]|date=March 30, 2016}}</ref><ref>{{cite web|last1=Higginbottom|first1=Stacey|title=Nvidia must be stoked: This startup is taking graphics chips corporate|url=http://fortune.com/2015/09/01/mapd-gpu-database/|publisher=[[Fortune (magazine)|Fortune]]|date=September 1, 2015}}</ref> The system works using [[Graphics processing unit|GPU technology]], which allows for rapid processing and mapping of [[big data]].<ref>{{cite web|last1=Matheson|first1=Rob|title=Split-second data mapping|url=https://news.mit.edu/2017/startup-mapd-fast-big-data-mapping-0111|publisher=[[Massachusetts Institute of Technology|MIT]]|date=January 11, 2017}}</ref> The idea came while Mostak was working at [[Massachusetts Institute of Technology|MIT]], he was researching [[Twitter|tweets]] with his queries taking hours or even days to complete using more traditional IT methods.<ref name=informationweek>{{cite web|last1=Babcock|first1=Charles|title=GPU Hardware Powers MapD Big Data Management|url=https://www.informationweek.com/infrastructure/pc-and-servers/gpu-hardware-powers-mapd-big-data-management/d/d-id/1327755|publisher=[[InformationWeek]]|date=December 23, 2016}}</ref>
HEAVY.AI's main offering is the Core database system, which was developed shortly after the company was founded.<ref>{{cite web|last1=Barinka|first1=Alex|title=Database Startup MapD Raises $10 Million From Google, Nvidia|url=https://www.bloomberg.com/news/articles/2016-03-30/database-startup-mapd-raises-10-million-from-google-nvidia|publisher=[[Bloomberg L.P.|Bloomberg]]|date=March 30, 2016}}</ref><ref>{{cite web|last1=Higginbottom|first1=Stacey|title=Nvidia must be stoked: This startup is taking graphics chips corporate|url=http://fortune.com/2015/09/01/mapd-gpu-database/|publisher=[[Fortune (magazine)|Fortune]]|date=September 1, 2015}}</ref> The system works using [[Graphics processing unit|GPU technology]], which allows for rapid processing and mapping of [[big data]].<ref>{{cite web|last1=Matheson|first1=Rob|title=Split-second data mapping|url=https://news.mit.edu/2017/startup-mapd-fast-big-data-mapping-0111|publisher=[[Massachusetts Institute of Technology|MIT]]|date=January 11, 2017}}</ref> The idea came while Mostak was working at [[Massachusetts Institute of Technology|MIT]], he was researching [[Twitter|tweets]] with his queries taking hours or even days to complete using more traditional IT methods.<ref name=informationweek>{{cite web|last1=Babcock|first1=Charles|title=GPU Hardware Powers MapD Big Data Management|url=https://www.informationweek.com/infrastructure/pc-and-servers/gpu-hardware-powers-mapd-big-data-management/d/d-id/1327755|publisher=[[InformationWeek]]|date=December 23, 2016}}</ref>
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After setting up a [[Graphics processing unit|GPU system]] and thorough testing, [[InformationWeek]] stated that the process was 75 times to 3,500 times faster than using a traditional CPU to process [[big data]].<ref>{{cite web|title=MapD closer to delivering "supercomputer in a box"|url=https://venturebeat.com/2015/03/06/mapd-closer-to-delivering-supercomputer-in-a-box/|publisher=[[VentureBeat]]|date=March 6, 2015}}</ref> Mostak wasn't alone in researching ways to process [[big data]]. After winning $100,000 at an [[Nvidia]]-ran competition,<ref>{{cite web|last1=Tiquet|first1=Alain|title=We’re Helping Entrepreneurs Like You Get Money, Get GPUs, and Get Going – Here’s How|url=https://blogs.nvidia.com/blog/2015/11/23/entrepreneurs/|publisher=[[Nvidia]]|date=November 23, 2015}}</ref> Nvidia's research in the space has led them to be able to process 750GB per second using a GPU system, when ran in conjunction with systems that OmniSci produce.<ref name=informationweek /> Other corporations such as [[IBM]] were also quoted to be using OmniSci's technology to develop GPU systems.<ref>{{cite web|last1=Taft|first1=Darryl|title=IBM Puts Nvidia Tesla K80 GPU on SoftLayer Cloud|url=http://www.eweek.com/cloud/ibm-puts-nvidia-tesla-k80-gpu-on-softlayer-cloud|publisher=[[eWeek]]|date=July 9, 2015}}</ref>
After setting up a [[Graphics processing unit|GPU system]] and thorough testing, [[InformationWeek]] stated that the process was 75 times to 3,500 times faster than using a traditional CPU to process [[big data]].<ref>{{cite web|title=MapD closer to delivering "supercomputer in a box"|url=https://venturebeat.com/2015/03/06/mapd-closer-to-delivering-supercomputer-in-a-box/|publisher=[[VentureBeat]]|date=March 6, 2015}}</ref> Mostak wasn't alone in researching ways to process [[big data]]. After winning $100,000 at an [[Nvidia]]-ran competition,<ref>{{cite web|last1=Tiquet|first1=Alain|title=We’re Helping Entrepreneurs Like You Get Money, Get GPUs, and Get Going – Here’s How|url=https://blogs.nvidia.com/blog/2015/11/23/entrepreneurs/|publisher=[[Nvidia]]|date=November 23, 2015}}</ref> Nvidia's research in the space has led them to be able to process 750GB per second using a GPU system, when ran in conjunction with systems that OmniSci produce.<ref name=informationweek /> Other corporations such as [[IBM]] were also quoted to be using OmniSci's technology to develop GPU systems.<ref>{{cite web|last1=Taft|first1=Darryl|title=IBM Puts Nvidia Tesla K80 GPU on SoftLayer Cloud|url=http://www.eweek.com/cloud/ibm-puts-nvidia-tesla-k80-gpu-on-softlayer-cloud|publisher=[[eWeek]]|date=July 9, 2015}}</ref>


Prior to the [[2016 United States presidential election|2016 presidential election]], HEAVY.AI created a visualization of political donations as a tool to attempt to predict certain outcomes in the election.<ref>{{cite web|last1=Janjigian|first1=Lori|title=Silicon Valley is betting its money on Hillary Clinton|url=http://uk.businessinsider.com/silicon-valley-donors-favor-hillary-clinton-over-trump-2016-11?r=US&IR=T|publisher=[[Business Insider]]|date=November 7, 2016}}</ref> In 2017, it was announced that HEAVY.AI would become one of the founding members of the GPU Open Analytics Initiative.<ref>{{cite web|last1=Cardoza|first1=Christina|title=The GPU Open Analytics Initiative, Red Hat OpenStack Platform 11, AIY Projects, and NVIDIA’s VRWorks SDK|url=https://sdtimes.com/ai/gpu-open-analytics-red-hat-openstack-sdtimes-may-8/|publisher=[[SD Times]]|date=May 8, 2017}}</ref>
Prior to the [[2016 United States presidential election|2016 presidential election]], HEAVY.AI created a visualization of political donations as a tool to attempt to predict certain outcomes in the election.<ref>{{cite web|last1=Janjigian|first1=Lori|title=Silicon Valley is betting its money on Hillary Clinton|url=https://www.businessinsider.com/silicon-valley-donors-favor-hillary-clinton-over-trump-2016-11?r=US&IR=T|publisher=[[Business Insider]]|date=November 7, 2016}}</ref> In 2017, it was announced that HEAVY.AI would become one of the founding members of the GPU Open Analytics Initiative.<ref>{{cite web|last1=Cardoza|first1=Christina|title=The GPU Open Analytics Initiative, Red Hat OpenStack Platform 11, AIY Projects, and NVIDIA’s VRWorks SDK|url=https://sdtimes.com/ai/gpu-open-analytics-red-hat-openstack-sdtimes-may-8/|publisher=[[SD Times]]|date=May 8, 2017}}</ref>


In September 2018, OmniSci was rebranded from MapD.<ref>{{cite web|title=MapD Rebrands to OmniSci|url=https://www.prnewswire.com/news-releases/mapd-rebrands-to-omnisci-300720094.html|publisher=[[PRNewswire]]|date=September 27, 2018}}</ref>
In September 2018, OmniSci was rebranded from MapD.<ref>{{cite web|title=MapD Rebrands to OmniSci|url=https://www.prnewswire.com/news-releases/mapd-rebrands-to-omnisci-300720094.html|publisher=[[PRNewswire]]|date=September 27, 2018}}</ref>

Latest revision as of 04:10, 13 August 2024

HEAVY.AI
FormerlyOmniSci, MapD
Company typePrivate
IndustrySoftware, Advanced Analytics
FoundedSeptember 2013 (2013-09)
FounderTodd Mostak, Thomas Graham
HeadquartersSan Francisco,
California
Area served
Worldwide
Products
  • SQL Engine and Visualization
Websitewww.heavy.ai

HEAVY.AI is an American-based software company, that uses graphics processing units (GPUs) and central processing units (CPUs) to query and visualize big data. The company was founded in 2013 by Todd Mostak and Thomas Graham and is headquartered in San Francisco, California.

The company has a range of products, which help process and visualize big data. HEAVY.AI has partnered with a number of organizations, such as Nvidia, to help build an infrastructure system which processes data much faster than traditional CPU methods. By using multiple GPU cards at once, HEAVY.AI's technology can process data at a much faster rate than CPU's.

HEAVY.AI raised funds in 2016 via a Series A, in 2017 via a Series B, and in 2018 via a Series C funding round.

History

[edit]

Todd Mostak and Thomas Graham founded HEAVY.AI, then named MapD, in 2013. Since their foundation, the company has focused on providing its services to a variety of markets, including government, public and private companies.[1][2]

HEAVY.AI's main offering is the Core database system, which was developed shortly after the company was founded.[3][4] The system works using GPU technology, which allows for rapid processing and mapping of big data.[5] The idea came while Mostak was working at MIT, he was researching tweets with his queries taking hours or even days to complete using more traditional IT methods.[6]

After setting up a GPU system and thorough testing, InformationWeek stated that the process was 75 times to 3,500 times faster than using a traditional CPU to process big data.[7] Mostak wasn't alone in researching ways to process big data. After winning $100,000 at an Nvidia-ran competition,[8] Nvidia's research in the space has led them to be able to process 750GB per second using a GPU system, when ran in conjunction with systems that OmniSci produce.[6] Other corporations such as IBM were also quoted to be using OmniSci's technology to develop GPU systems.[9]

Prior to the 2016 presidential election, HEAVY.AI created a visualization of political donations as a tool to attempt to predict certain outcomes in the election.[10] In 2017, it was announced that HEAVY.AI would become one of the founding members of the GPU Open Analytics Initiative.[11]

In September 2018, OmniSci was rebranded from MapD.[12]

In March 1, 2022, OmniSci rebranded to Heavy.AI.[13]


Funding

[edit]

In 2016, it was announced that HEAVY.AI had raised capital via a Series A funding round,[14] believed to be $10 million.[15] A number of major participants were listed in the round, which was led by In-Q-Tel.[16] Other participants included Nvidia, Vanedge Capital, and Verizon Wireless.[15] Nvidia became interested in HEAVY.AI, after the company won $100,000 from Nvidia at their GPU Ventures contest.[17]

The following year, HEAVY.AI raised capital via a Series B funding round.[18] The round secured $25 million in additional funding for OmniSci, with New Enterprise Associates, Nvidia and Verizon leading the funding round.[19]

In October 2018, HEAVY.AI secured $55 million through a Series C funding round led by Tiger Global Management,[20] and with the participation of existing investors, including In-Q-Tel, New Enterprise Associates, Vanedge Capital, Nvidia and Verizon Ventures.[21]

[edit]

References

[edit]
  1. ^ Wadhwa, Tina (September 22, 2016). "I listened to 82 finance startup pitches — here's what I learned about where Wall Street is heading". Business Insider.
  2. ^ McKenna, Brian. "Silicon Valley startups home in on pressing value from data". Computer Weekly.
  3. ^ Barinka, Alex (March 30, 2016). "Database Startup MapD Raises $10 Million From Google, Nvidia". Bloomberg.
  4. ^ Higginbottom, Stacey (September 1, 2015). "Nvidia must be stoked: This startup is taking graphics chips corporate". Fortune.
  5. ^ Matheson, Rob (January 11, 2017). "Split-second data mapping". MIT.
  6. ^ a b Babcock, Charles (December 23, 2016). "GPU Hardware Powers MapD Big Data Management". InformationWeek.
  7. ^ "MapD closer to delivering "supercomputer in a box"". VentureBeat. March 6, 2015.
  8. ^ Tiquet, Alain (November 23, 2015). "We're Helping Entrepreneurs Like You Get Money, Get GPUs, and Get Going – Here's How". Nvidia.
  9. ^ Taft, Darryl (July 9, 2015). "IBM Puts Nvidia Tesla K80 GPU on SoftLayer Cloud". eWeek.
  10. ^ Janjigian, Lori (November 7, 2016). "Silicon Valley is betting its money on Hillary Clinton". Business Insider.
  11. ^ Cardoza, Christina (May 8, 2017). "The GPU Open Analytics Initiative, Red Hat OpenStack Platform 11, AIY Projects, and NVIDIA's VRWorks SDK". SD Times.
  12. ^ "MapD Rebrands to OmniSci". PRNewswire. September 27, 2018.
  13. ^ "OmniSci Announces Rebrand to HEAVY.AI to Mark a New Era of Advanced Analytics for Time-sensitive Decision-making at Enterprise Scale". Heavy.AI. March 1, 2022.
  14. ^ Zakrzewski, Cat (March 30, 2016). "MapD Locates $10 Million Series A for Faster Databases". Wall Street Journal.
  15. ^ a b Novet, Jordan (March 30, 2016). "Nvidia backs GPU-powered data analytics tool MapD in $10 million round". VentureBeat.
  16. ^ Zakrzewski, Cat (October 19, 2016). "CIA's In-Q-Tel Invests In Data Analytics Company MapD". Wall Street Journal.
  17. ^ Takahashi, Dean (March 27, 2018). "Nvidia: 'Every cloud computing software maker is building on top of CUDA'". VentureBeat.
  18. ^ Darrow, Barb (March 29, 2017). "This Data Crunching Company Just Scored A Big New Investment". Fortune.
  19. ^ Magistretti, Berenice (March 29, 2017). "GPU database startup MapD raises $25 million led by NEA". VentureBeat.
  20. ^ Marinova, Polina (October 4, 2018). "Term Sheet -- Thursday, October 4". Fortune.
  21. ^ "OmniSci Secures $55M in Series C Funding". Finsmes.com. October 3, 2018.
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