1
Spatial Front
Bethesda, Maryland, United States
Offering IT services along with geospatial technology, system integration, software development, enterprise infrastructure, data analytics and more
- Revenue
- $59.8M
- Year founded
- 2008
- Team size
- 381
Top 7 Big Data Analytics Software Companies With $10M–$100M Revenue (September 2026)
As of September 2026, Latka tracks 7 big data analytics software companies with $10M–$100M in annual revenue. They have combined revenues of $216.3M and employ 1.1K people. They have raised $133.2M and serve 500K 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.
What Big Data Analytics Software Companies do
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.
- Companies
- 7
- Revenue
- $216.3M
- Funding
- $133.2M
- Employees
- 1.1K
Filters
Sorting: Highest -> Lowest
Top Big Data Analytics Software Companies With $10M–$100M Revenue
Showing 7 of 7 companies ranked by annual revenue.
2
Lyzer
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.
- Revenue
- $50M
- Customers
- 500K
- Year founded
- 2024
- Funding
- $11.7M
- Team size
- 56
3
Qa Technologies, Inc.
Hampton, New Hampshire, United States
QAT Global is an information technology company offering cloud computing, big data, analytics, and integration solutions.
- Revenue
- $30M
- Year founded
- 1995
- Team size
- 53
- Revenue
- $25.1M
- Year founded
- 2014
- Team size
- 208
5
Ocient
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.
- Revenue
- $24.6M
- Year founded
- 2016
- Funding
- $65M
- Team size
- 172
6
GigaSpaces
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.
- Revenue
- $13.8M
- Year founded
- 2000
- Funding
- $46M
- Team size
- 125
- Growth
- 35.13%
7
Talon Aerolytics
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.
- Revenue
- $13.1M
- Year founded
- 2015
- Funding
- $10.5M
- Team size
- 58
Frequently asked questions about Big Data Analytics Software Companies With $10M–$100M Revenue
How many big data analytics software companies with $10M–$100M in annual revenue are there?
Latka tracks 7 big data analytics software companies with $10M–$100M in annual revenue. Together they generate $216.3M in annual revenue and employ 1.1K people.
Which big data analytics software company with $10M–$100M in annual revenue is the largest?
Spatial Front is the largest, with $59.8M in annual revenue, founded in 2008.
How much revenue does a typical big data analytics software company with $10M–$100M in annual revenue make?
The average big data analytics software company in this list makes $30.9M a year, across 7 companies with reported revenue. They serve 500K customers combined.
Who are the leading Big Data Analytics software vendors with $10M–$100M in annual revenue?
Ranked by annual revenue, the leaders are Spatial Front, Lyzer, Qa Technologies, Inc., Kentik and Ocient.
How much funding have big data analytics software companies with $10M–$100M in annual revenue raised?
The 7 big data analytics software companies with $10M–$100M in annual revenue tracked here have raised $133.2M in disclosed funding between them.
Related IT Infrastructure Software categories
Inclusion Criteria
- 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