As of May 2026, there are 20 SaaS companies in Big Data Analytics Software. They have combined revenues of $348.6M and employ 1.8K people. They have raised $1.1B and serve 500.1K customers combined.
Big Data Analytics Software encompasses tools and systems designed to collect, process, and analyze extensive and rapidly changing data sets. These platforms enable organizations to derive meaningful insights from large volumes of structured and unstructured data, facilitating decision-making and strategic planning. Typical use cases include predictive analytics, customer behavior analysis, operational optimization, and trend identification. Key features of Big Data Analytics Software often include data integration, real-time analytics, machine learning capabilities, and advanced visualization tools. Users typically range across various sectors, including IT, marketing, finance, and operations, with individuals like data scientists, business analysts, and decision-makers engaging with these systems to enhance their organizational intelligence. The ability to analyze data at scale not only informs business strategies but also drives innovation across industries.
Sorting: Highest -> Lowest
Showing 10 of 8 companies ranked by annual revenue.
Palo Alto, California, United States
SambaNova is the leading Enterprise AI company that delivers a full-stack infrastructure from silicon to software, specializing in machine learning and big data analytics platforms.
Bethesda, Maryland, United States
Offering IT services along with geospatial technology, system integration, software development, enterprise infrastructure, data analytics and more
Lisbon, Portugal
Lyzer is an AI-powered data analytics and decision intelligence platform that helps businesses analyze data, generate insights, and automate data-driven decisions without requiring deep technical expertise.
Hampton, New Hampshire, United States
QAT Global is an information technology company offering cloud computing, big data, analytics, and integration solutions.
Chicago, Illinois, United States
Provider of a big data platform intended to offer rapid analysis of the world's largest datasets. The company's big data platform works on large datasets that are measured in tens of terabytes, petabytes or exabytes with trillions or quadrillions of rows, as well as focuses on ingressing billions of rows per second, filtering and computing aggregate results at rates up to trillions of rows per second, enabling organizations to harness the untapped power of large datasets, at scale and speed.
Herziliyah, Central, Israel
GigaSpaces helps enterprises apply AI to real-time, structured operational data — enabling spontaneous, natural language conversations that accelerate decision-making, improve agility in unexpected situations, and surface opportunities and risks in everyday business. With over two decades of experience powering mission-critical systems, GigaSpaces is a pioneer in real-time data technology and a trusted foundation for data-driven services across industries, including finance, travel, telecom, and insurance. Headquartered in the US, with offices in Europe and Israel, GigaSpaces helps organizations turn operational data into decisions that are timely, secure, and scalable.
West Point, Georgia, United States
Operator of an infrastructure data capture and analytics platform intended to be used for commercial applications. The company's platform offers cloud-based content management, HD videos and photos and data analytics, enabling clients to create value by delivering data efficiently and effectively through our content management system.
- Must provide capabilities for analyzing large and complex data sets - Must support real-time data processing and analytics - Must include data visualization tools to present insights effectively - Must offer integration with other data sources and tools - Not just traditional reporting; must also enable predictive and prescriptive analytics - Should allow for machine learning model deployment and management - Must cater to multiple industries and use cases, including operational, customer, and predictive analytics
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