Data is now the world’s most valuable commodity, and San Francisco big data companies are here to help businesses strike it rich. “Big data” essentially refers to information of greater varieties, increasing volumes and higher velocities. Basically, our information is becoming bigger, faster and more diverse than ever before. Big data companies help businesses harness the underlying power of their ever-growing mounds of data to address pressing issues and craft future strategy.
San Francisco is home to some of the most innovative big data firms in the world. These companies are making sense of data, no matter the industry or the technology. They’re connecting dots, spurring breakthroughs and leading to more efficient processes. Check out 15 of the most impactful big data companies in San Francisco.
Industry: Marketing Tech + Adtech
Founded: 2011
What they do: Segment makes is easy for businesses to unify and collect data from all their marketing and advertising tools. Rather than relying on data from separate platforms to holistically inform marketing and advertising decisions, teams use Segment to centralize data from more than 250 platforms to give a truly in-depth view of customer data and analytics. Segment’s big data API is used by global brands like IBM, DigitalOcean, Levi’s and Atlassian to gain holistic insights into their campaigns.
Industry: Adtech
Founded: 2012
What they do: LiveRamp’s big data platform combines data from all sources, devices and people in a company’s ecosystem and houses it under one single source of truth. Marketing teams have a much easier time running omnichannel campaigns, gathering customer data insights and measuring ROI by connecting data silos on the LiveRamp platform. The publicly traded company has helped businesses, like Google, United Airlines, Hulu and Whole Foods, streamline their marketing data management practices and better identify their audiences.
Industry: Business Intelligence + Software + Cloud
Founded: 2010
What they do: Developers use MapBox’s live location big data platform to power their live map networks. Need a rideshare? Want to check the weather where you’re at? Maybe you'd like to receive local news? Companies like DoorDash, The Weather Channel, Snapchat and CNN are able to get you the most up-to-date information no matter where you’re at with MapBox’s live location big data platform.
Industry: Mobile
Founded: 2010
What they do: App Annie’s mobile marketing big data and analytics platform gives app makers better insights into performance standards. The company’s suite of data tools help app makers gain better insights into everything ranging from user engagement and advertising metrics to organic user acquisition and how to better monetize their app. The App Annie platform currently uses data from more than one million anonymized apps to give users a well-rounded, real-time look into the industry.
Industry: Analytics + Software
Founded: 2011
What they do: MemSQL’s database powers enterprise applications and analytics platforms. The company’s big data platform is designed to accelerate the time databases take to ingest information and answer queries. Additionally, MemSQL is used to streamline a company’s data lakes and scale their predictive analytics, machine learning and AI operations. Uber, Verizon, Samsung and Monday.com all use MemSQL to power the applications that capture their data.
Industry: Analytics + Mobile + Software
Founded: 2012
What they do: Amplitude’s big data analytics platform gives enterprises insights into customer behavior, which helps build a more customer-focused product. The Amplitude customer data tools give granular and individualized insights into customer base behaviors, so enterprises can craft strategy, improve user engagement, optimize sales conversion rates and boost user retention. The database currently has more than 7.5 trillion data points on customer behavior that global brands like Instacart, PayPal and CapitalOne all use to create customer-focused products.
Industry: Analytics + Software
Founded: 2012
What they do: Trifacta understands that big data is messy. That’s why their platform helps accelerate data wrangling, also known as the cleaning, preparation and management of a company’s data. The Trifacta platform takes the information from an enterprise’s cloud data lakes and warehouses and wrangles it to improve everything from time-to-analysis to pattern discovery.
Industry: Business Intelligence + Analytics
Founded: 2007
What they do: Crunchbase is a big data platform that offers detailed business information for both private and public companies. The platform gives users insights into specific company information that ranges from funding and investors to monthly web traffic and revenue estimates. Crunchbase gathers its massive amount of business data through a combination of machine learning, data science and their community members.
Industry: Analytics + Software
Founded: 2014
What they do: StreamSets DataOps platform operationalizes data integration for big data applications. The company’s suite of tools help businesses manage their data lakes to streamline pipelines, monitor runtime performance and protect their sensitive information in real-time.
Industry: Developer Tools + Analytics
Founded: 2011
What they do: Mode’s platform allows developers to analyze raw or modeled big data with SQL, Python or R without having to move between various tools. The platform allows for developers to quickly sift through data warehouses and easily write queries with its autocomplete feature. Lyft, Twitch, and Zillow all use Mode’s platform to manage their big data and speed up software development.
Industry: Customer Service + Sales + Software
Founded: 2015
What they do: Chorus.ai is a conversation intelligence platform that captures insights from conversations with customers and uses the data to optimize future calls. The platform records calls and uses AI to pull out the data that can help sales and customer service teams improve their talk tracks, increase productivity and train new employees efficiently. Bugcrowd, Placester and Growbots are just a few of the companies that use Chorus.ai to gather data to optimize their sales and customer service processes.
Industry: Edtech
Founded: 2012
What they do: Clever builds modern learning softwares that help to educate students and extrapolate their learning data. Students, using Clever’s single sign-on platform, have access to a wide range of learning apps and administrative tools that help boost their education experiences. Teachers and school administrators also use these apps to gather and monitor thousands of data points on each student to identify learning curves and improve upon personalized lesson planning.
Industry: Real Estate
Founded: 2013
What they do: HouseCanary uses big data to provide detailed and accurate real estate valuations. The platform uses proprietary analytics and data on more than 100 million U.S. homes to formulate current prices and future forecasts for individual properties, whole neighborhoods and the overall real estate market.
Industry: Software + Analytics
Founded: 2010
What they do: Quid is a contextual AI platform that takes content (news, product reviews, online forums, etc.) and turns it into digestible, visualizable data points. The platform analyzes thousands of pieces of content, sifts through the mess of big data to find the pertinent information and formulates it into reports on vital connections, trends and industry insights. Adidas, Intel and The New York Times are just a few of the well-known brands using Quid’s contextual data to influence their business decisions.
Industry: Real Estate
Founded: 2014
What they do: Wheelhouse uses real-time real estate data insights to help inform short-term rental owners on how to accurately price their properties. The company’s platform analyzes more than 10 billion data points (including daily hotel and short-term rental booking trends in the area) to inform renters on how their pricing strategies compare with comparable listings. By using Wheelhouse, renters constantly price their properties competitively, helping maximize potential revenue and decrease vacancy periods.
