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Top 2 Big Data Integration Platforms Companies (September 2026)

As of September 2026, Latka tracks 2 big data integration platforms companies. They have combined revenues of $3.3M and employ 27 people. They have raised $600K and serve 100K customers combined.

Every company below sells big data integration platforms 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 Integration Platforms Companies do

Big Data Integration Platforms encompass a category of software solutions designed to facilitate the seamless merging of large datasets from diverse sources. These platforms enable organizations to gather, process, and analyze vast amounts of data, turning it into actionable insights that drive decision-making. Common use cases include customer data integration, real-time analytics, and data unification for business intelligence applications. Typically, these platforms offer features such as data extraction, transformation, loading (ETL), data quality management, and automation capabilities. They cater to a variety of buyer personas, primarily targeting IT professionals, data analysts, and business intelligence teams who require robust solutions for managing complex data landscapes and enhancing data-driven strategies.

Companies
2
Revenue
$3.3M
Funding
$600K
Employees
27

Filters

Sorting: Highest -> Lowest

Filters

Top Big Data Integration Platforms Companies by revenue

Showing 2 of 2 companies ranked by annual revenue.

1CloudQuery logo
CloudQuery

NYC, New York, United States

The open source high-performance data integration platform for security and infrastructure teams

Revenue
$3M
Year founded
2021
Team size
27
2Free Google Maps Extractor & Scraper with Email | GMPlus logo
Free Google Maps Extractor & Scraper with Email | GMPlus

United Kingdom

Extract business data from Google Maps and export structured results to CSV. This free Google Maps extractor helps you search businesses by category and location, then collect business names, phone numbers, available emails, websites, addresses, ratings, opening hours, categories, and other supported fields. Use the organized data for business research, prospecting, lead generation, competitor analysis, and other local market workflows without coding.

Revenue
$300K
Customers
100K
Year founded
2022
Funding
$600K

Frequently asked questions about Big Data Integration Platforms Companies

How many big data integration platforms companies are there?

Latka tracks 2 big data integration platforms companies with reported revenue. Together they generate $3.3M in annual revenue and employ 27 people.

Which big data integration platforms company is the largest?

CloudQuery is the largest, with $3M in annual revenue, founded in 2021.

How much revenue does a typical big data integration platforms company make?

The average big data integration platforms company in this list makes $1.6M a year, across 2 companies with reported revenue. They serve 100K customers combined.

Who are the leading Big Data Integration platforms vendors?

Ranked by annual revenue, the leaders are CloudQuery and Free Google Maps Extractor & Scraper with Email | GMPlus.

How much funding have big data integration platforms companies raised?

The 2 big data integration platforms companies tracked here have raised $600K in disclosed funding between them.

Related IT Infrastructure Software categories

Inclusion Criteria

- Must provide capabilities for extracting, transforming, and loading (ETL) data from multiple sources. - Should enable users to integrate large volumes of structured and unstructured data for analysis. - Must include tools for data quality management and validation processes. - Should offer automation features to streamline data integration workflows. - Targeted at IT departments and business analysts engaged in data management and analytics. - Not limited to simple data aggregation; must also support complex data transformations and unification.