In-house developers and software vendors leverage open-source MapD Core to accelerate existing analytic applications or to create tomorrow’s extreme analytic applications.

Develop New Apps on Open-Source

Developers want to create tomorrow’s lightning-fast applications. We open-sourced our MapD Core SQL engine to make its hyper-speed processing available to that community of innovators.

Boost the Performance of Existing Apps

Most enterprise applications were architected during an earlier era, before GPUs were an option. “Lift and shift” those onto the MapD Core SQL engine and dramatically improve their performance.

Embed MapD Immerse Visual Analytics

MapD displays data for real-time interaction. Companies can increase customer engagement by offering embedded MapD to valuable customers wanting to explore their own data.

ClimaCell: Making Micro-Weather Forecasts Work

The Challenge

Climacell's HyperCast product for micro-weather forecasts was already generally available. The engineering team had trouble overlaying precipitation data on a map in a highly performant and visually appealing way. Its underlying data architecture couldn’t query data and render geo-charts quickly enough to obtain the company's product vision.

MapD Solution

MapD’s Core SQL and rendering engines helped ClimaCell bridge the gap for visual analytics. Now, ClimaCell weather predictions are accurate down to the level of individual city blocks. Signals transmitted from cell towers enable HyperCast to refresh the data as often as once a minute. MapD’s unmatched query speed and unique rendering engine help the company create and display highly granular forecasts for its customers.

Second Measure: Accelerating Financial Analytics

The Challenge

Second Measure built its business analyzing credit card transactions at a volume that amounted to about 1% of all U.S. consumer spending. The company aimed to provide those analytics to financial analysts and equities researchers seeking insight into public and private companies. Second Measure wanted to accelerate performance to provide a better experience to its time-conscious clients.

MapD Solution

Second Measure uses MapD to accelerate its queries that analyze each transaction from each customer for a given company. Now it delivers analytics so fast that its clients can: spot inflections in businesses as they happen, identify every week's fastest-growing companies, and see the latest company performance before it's announced.

Tutela: Showing Carriers Network Anomalies

The Challenge

Tutela set out to build a crowd-sourced solution for visualizing mobile data on network quality. Once its data reached extreme volumes, it became too much for traditional data visualization tools. It took days of labor to gain minor insights from an inherently valuable data set. Tutela chose to embed MapD’s visual analytics, offering its customers an interactive portal to explore network performance data on their own.

MapD Solution

Now Tutela's software is installed and runs on over 200 million cell phones globally to measure mobile network signal quality. Tutela’s mobile telecom clients view the health of their networks using MapD Immerse. This helps those telcos with operational analytics to improve their coverage and provide a better subscriber experience.

Pactriglo: Locating Opportunities for Urban Housing Development

The Challenge

Pactriglo was founded on the premise that maximizing developer utilization of existing zoning could circumvent the lengthy political process and help solve LA’s housing crisis. Existing platforms, such as ZIMAS, NavigateLA, and LADBS, were unable to dive into millions of data points simultaneously, or to interactively explore the data by zone, down to the street level. Pactriglo's custom real estate application could only meet that objective by harnessing MapD’s power to query and visually explore regional housing data much faster than existing tools for geospatial analytics.

MapD Solution

Pactriglo empowers its building developer customers by giving them MapD’s visual analytics and SQL engine so they can slice and dice the dataset in its entirety. This eliminates the need for pre-aggregation, and Pactriglo users see results in milliseconds. They can easily cross-filter the data by the features that matter: zoning, sub-zoning, utilization, or construction activity.