As of September 2026, Latka tracks 7 big data analytics software companies with $1M–$5M in annual revenue. They have combined revenues of $14.9M and employ 188 people. They serve 100 customers combined.
Every company below sells big data analytics software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
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 7 of 7 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.
Chandler, Arizona, United States
Cloud Computing Technologies provides applications, data analytics, network security, AI, machine learning, SaaS and PaaS services.
Singapore, Singapore, Singapore
Togglr is a Hybrid Multicloud Digital Services Platform that built on AI technology for migration, disaster recovery and backup, orchestration, and analytics services that enables digital transformation, along with data protection.
Makati City, Metro Manila, Philippines
Comfac Technology Options (CTO) is one of the leading information technology (IT) companies in the Philippines, offering a full range of technology products, solutions and services, such as, but not limited to Infrastructure as a Service (Private/Public and Hybrid Cloud), Managed Infrastructure Services, Big Data & Analytics and Platform-as-a-Service solutions.
Addison, Texas, United States
VSI is a Storage Analytics on Demand- SaaS that provides a visual health analysis of your complex SAN environment in minutes.
Bellevue, Washington, United States
Developer of an in-memory computing software. The company develops an in-memory computing platform that accelerates application performance and enhances operational data analysis.
Herzliya, Israel
Developer of continuous monitoring system intended to convert cellular networks big data into real-time valuable insights. The company's system facilitates automated online monitoring of different characteristics of the RF mobile networks relating to RF radiation, spectrum, coverage, and quality-of-service parameters thereby enabling authorities to monitor the real-time and historical locations, movements, and communication activity with improved accuracy, immediacy, and flexibility.
Latka tracks 7 big data analytics software companies with $1M–$5M in annual revenue. Together they generate $14.9M in annual revenue and employ 188 people.
nominal.io is the largest, with $4.7M in annual revenue, founded in 2022.
The average big data analytics software company in this list makes $2.1M a year, across 7 companies with reported revenue. They serve 100 customers combined.
Ranked by annual revenue, the leaders are nominal.io, Cloud Computing Technologies, Togglr, Comfac Technology Options and Visual Storage Intelligence.
- 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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