As the torrent of big data flows in from more sources, in greater volumes, analysts and data scientists are increasingly frustrated with lack of performance from mainstream analytics tools that were designed in a past era.
MapD allows our users to exercise unbounded curiosity when exploring data. To achieve this, a new kind of analytics needed to be invented - what we call Extreme Analytics - delivering extreme speed, extreme scale, and extreme interactivity.
The journey towards discovery is not linear. Nor should it be one of mindless meandering. We want everyone to be curious again and explore any hypothesis – to ask question upon question, without curiosity-defeating latency. So we designed a platform that smooths all the obstacles to exploration, making you feel like you are one with your data.
SQL is the language of analytics. MapD supports standard SQL semantics but returns query results hundreds of times faster than mainstream SQL engines.
When you render millions of shapes or billions of points on the GPU, MapD sends a PNG image to the browser. Visually interact with big data, without data movement.
Location data is now a first-class citizen for business intelligence, a steel thread that combines BI and GIS, too long treated as separate and distinct types of analysis.
MapD pushes the boundaries of what’s possible with GPU accelerated analytics. MapD Core is the first SQL engine to natively harness GPU computing for analytics, and we open sourced that technology. We were the first to deliver truly interactive, real-time analytics and visual interaction with multi-billion row data sets. We made GPU analytics available in the cloud. And MapD was first to deliver geo data calculations and server-side rendering of polygons on GPUs.
MapD Core compiles SQL queries and processes them in parallel across thousands on GPU cores, for millisecond results on billions of records.
MapD Immerse makes you one with your data. Interact with any map, chart or graph, all cross-filtered in context with each other and refreshed in real-time.
Location data is now Big Data. MapD was created for geospatial analysis at scale and renders billions of points or millions of polygons on interactive maps.
When your data grows, your need for analytical speed will not diminish. You cannot settle for slow performance at scale. MapD is future-proof, with linear scaling of hardware, high availability across many servers, and a cloud SaaS option to offload peak demand or as a replacement for analytics platforms in your the data center.
MapD’s distributed architecture allows your IT team to add servers and maintain query performance even as the data grows to extreme scale.
MapD replicates data across multiple servers for resiliency. As data and use cases grow, add new servers to maintain millisecond performance.
MapD Cloud X is a managed service running on the major public cloud service providers, saving you the responsibility of procuring GPU hardware.
Software deployment and data ingestion are necessary steps to delivering a platform that changes how you do analytics. We want you to get that value immediately, so we created a real time analytical platform that makes implementation, user adoption, and data ingestion easy. MapD gives you immediate value for your investment.
Other analytics platforms using GPUs require weeks of professional services. MapD requires no tuning, and implementation takes hours.
MapD is fast and interactive, but we also made it easy and intuitive. You’ll be building dashboards in minutes, without any training.
Data is everywhere, and MapD lets you ingest millions of records per second, using familiar ingest technologies like Kafka, JDBC, or Sqoop.
It’s no accident that the most important Big Data platforms are open source. Open source is the fastest path to innovation. Our open-source core invites that innovation, accelerates our collaboration for end-to-end data science pipelines on the GPU and protects our customers from locking themselves into one approach.
MapD open sourced our MapD Core SQL engine because we know our code is solid. We wanted to put it on the fastest path to innovation.
The open source Apache Arrow framework for sharing in-memory data connects feature engineering in MapD to partner ML technologies.
We will always work to make MapD Core better. Rather than lock customers in with proprietary code, we work every day to make our SQL engine better, in the open.