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Top 2 Big Data Processing And Distribution Systems Companies Under $1M Revenue (September 2026)

As of September 2026, Latka tracks 2 big data processing and distribution systems companies under $1M in annual revenue. They have combined revenues of $1.2M and employ 12 people.

Every company below sells big data processing and distribution systems 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 Processing And Distribution Systems Companies do

Big Data Processing and Distribution Systems refer to technologies that facilitate the collection, storage, processing, and distribution of vast amounts of data across multiple platforms. These systems often enable real-time data insights and analytics, which can be critical for businesses seeking to make data-driven decisions. Common use cases include predictive analytics, customer experience enhancement, and operational efficiency improvements. Typically, these systems are utilized by IT professionals, data scientists, and business analysts who require robust data management capabilities. They often feature batch processing, stream processing, and various analytics tools. Integration with existing IT infrastructures and support for distributed computing are also crucial, allowing organizations to scale their operations and handle large datasets effectively.

Companies
2
Revenue
$1.2M
Funding
-
Employees
12

Filters

Sorting: Highest -> Lowest

Filters

Top Big Data Processing And Distribution Systems Companies Under $1M Revenue

Showing 2 of 2 companies ranked by annual revenue.

1Vitesse Data logo
Vitesse Data

United States

Developer of a SaaS based data processing software designed to unleash the power of modern CPUs. The company's software uses open source databases to accelerate Generic Probe Database Browser (GPDB) for the data warehouse, enabling users to enhance their system's efficiency.

Revenue
$765.7K
Year founded
2014
Team size
2
2cloud infra LLC logo
cloud infra LLC

Bangalore, Karnataka, India

CloudInfra builds soft infrastructure services on the cloud. Our flagship product helps users use linux power tools (grep, sed, awk, ...) on their data stored on cloud. Imagine running a grep on Tbs of data stored on S3 with in few seconds. Not just that, we allow you to run map-reduce kind of operations all in your familiar linux commands, no java/pig scripts to learn. Cloudinfra is founded by Ex-Google guys, with immense experience handling big data and machine learning.

Revenue
$439.6K
Year founded
2012
Team size
10

Frequently asked questions about Big Data Processing And Distribution Systems Companies Under $1M Revenue

How many big data processing and distribution systems companies under $1M in annual revenue are there?

Latka tracks 2 big data processing and distribution systems companies under $1M in annual revenue. Together they generate $1.2M in annual revenue and employ 12 people.

Which big data processing and distribution systems company under $1M in annual revenue is the largest?

Vitesse Data is the largest, with $765.7K in annual revenue, founded in 2014.

How much revenue does a typical big data processing and distribution systems company under $1M in annual revenue make?

The average big data processing and distribution systems company in this list makes $602.7K a year, across 2 companies with reported revenue.

Who are the leading Big Data Processing And Distribution systems vendors under $1M in annual revenue?

Ranked by annual revenue, the leaders are Vitesse Data and cloud infra LLC.

Related IT Infrastructure Software categories

Inclusion Criteria

- The software must facilitate the collection, processing, and analysis of large datasets. - It should support both batch and real-time data processing capabilities. - Systems must allow for data distribution across multiple environments or nodes. - It should provide analytics tools that enable users to extract meaningful insights from data. - Target users must include IT professionals, data analysts, or business analysts. - Not just data storage solutions; must also enable data processing and analytics.