As of May 2026, there are 68 SaaS companies in Big Data Software. They have combined revenues of $2.9B and employ 15.4K people. They have raised $4.1B and serve 20M customers combined.
Big Data Software encompasses tools and platforms designed to store, manage, analyze, and visualize large volumes of data that traditional data processing software cannot handle effectively. These solutions enable organizations to derive insights from various data sources, helping in making data-driven decisions. Primary use cases include predictive analytics, operational intelligence, customer behavior analysis, and fraud detection, among others. Typical features of Big Data Software include data ingestion, storage, processing frameworks, and visualization capabilities. Users range from data scientists and business analysts to IT professionals who are responsible for managing the data lifecycle and ensuring data security. Common buyer personas include professionals from finance, marketing, operations, and research and development, all seeking to leverage big data for enhanced strategic decision-making.
Sorting: Highest -> Lowest
Showing 10 of 16 companies ranked by annual revenue.
Austin, Texas, United States
Nominal is a data infrastructure and analytics platform helping hardware engineering teams quickly and reliably test and validate critical systems. It powers mission-critical engineering work across aerospace, energy, automotive, and defense with automation, analytics, and operations in one unified solution.
Rajkot, Gujarat, India
Improwised Technologies is a leading IT company founded with a desire to become a top software development company in scalable, data-intensive, and cloud-native applications.
Austin, Texas, United States
Pratexo is an intelligent edge-computing and distributed cloud platform for Artificial Intelligence, the Internet of Things, and Industry 4.0 applications.
London, England, United Kingdom
NetMind provides cutting-edge AI infrastructure, offering streamlined access to inference services, AI -as-a-Service (AIaaS), and high-performance GPU resources. Designed to power scalable AI applications, our platform simplifies deployment and management of sophisticated AI workflows—enabling teams to move swiftly...
Palo Alto, California, United States
Born from decades of expertise in elite Israeli intelligence forces, Datorios combines deep expertise in real-time technology and intelligence to revolutionize observability for real-time applications, empowers businesses to operate with confidence in the real-time era. The rise of real-time applications, driven by fraud detection, on-demand services, IoT, and agentic AI, demands a new approach. However, many companies still rely on end users and actual revenue as the basis for their monitoring. These companies lack robust observability solutions, leaving them blind to critical data problems and application failures until it’s too late. This is a billion-dollar problem across the data industry. Datorios fills this critical gap by providing the first comprehensive observability platform designed for real-time applications. By correlating data, code, and metrics, Datorios empowers organizations to proactively identify and address issues, ensuring data validity and resilient infrastructure.
Bristol, United Kingdom, United Kingdom
From cutting-edge AI and Life Sciences, to Asset Management and large-scale Enterprise transformation, YellowDog helps accelerate your innovation. The YellowDog Platform seamlessly optimises the full potential of compute across hybrid and multi-cloud environments, ensuring technology teams can provision...
Beijing, Beijing, China
SphereEx is a database software provider that builds distributed data infrastructures with the help of cloud and big data technologies.
Auckland, New Zealand
aZen is building the computing infrastructure for ubiquitous AI. It offers a scalable computing layer designed to power Web3 applications, AI services, and data analytics. The aZen ecosystem combines protocol-level AI orchestration, enterprise-grade hardware, and an integrated application hub—bridging DePIN and DeFAI into one seamless framework.
London, United Kingdom
Gensyn is a machine learning computing protocol that connects all of the machine learning-capable compute hardware to enable the training of deep learning models. It focuses on decentralizing computing power to advance the field of machine learning.
- Product must be capable of handling and processing large volumes of structured and unstructured data. - Must provide advanced analytics features such as machine learning or predictive modeling. - Should include data visualization tools to present insights clearly and effectively. - Must support integration with various data sources and formats. - Not just data storage; must also offer actionable insights and analytics capabilities.
Each Tuesday, we reverse-engineer a real SaaS company's revenue, profit, CAC, funnels, and its top growth tactic.
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