AI Buyer Insights:

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

List of Apache Hadoop Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
2K Games Professional Services 3000 $930M United States Apache Software Apache Hadoop Database Management 2017 n/a
In 2017, 2K Games deployed Apache Hadoop to establish a centralized Big Data Infrastructure supporting the companys analytics and data engineering functions. Apache Hadoop was positioned as the primary distributed storage and processing backbone to consolidate ingestion, transformation, and manipulation of data from across the organization for the analytics team. The implementation centered on Hadoop as the storage and compute foundation, paired with category aligned processing frameworks to host ETL and ELT pipelines that ingest from REST APIs and internal systems. The analytics engineering responsibilities emphasized building reusable, scalable data models, managing ETL processes into data warehouses, scheduling jobs to pull data from APIs, and maintaining internal databases used for reporting and dashboarding. Integrations were explicitly aligned to the existing toolset documented in hiring and engineering notes, including AWS EC2 and S3 for cloud compute and object storage, Amazon EMR and Spark for distributed processing, and Redshift and columnar storage for analytical warehousing. The deployment also interfaced with SQL and NoSQL databases, Pentaho style ETL patterns, and visualization backends such as Tableau to support dashboarding and access control for analytics consumers. Governance and operational changes focused on instituting continuous integration pipelines, enforcing software development best practices on the analytics team, and formalizing access control and job scheduling for reporting workloads. Implementation emphasis was on maintainability and scalability, enabling data engineers and data scientists to build, test, and deploy pipelines while centralizing data ingestion, transformation, and model orchestration within the Big Data Infrastructure.
3M Manufacturing 61500 $24.6B United States Apache Software Apache Hadoop Database Management 2012 n/a
In 2012, 3M deployed Apache Hadoop as Big Data Infrastructure to underpin the Data Science Lab's clinical data analytics platform. The Data Science Lab was responsible for leading independent R&D projects in machine learning and advanced statistical analysis of healthcare data, extracting knowledge from large and diverse datasets and building predictive models and novel algorithms for production deployment on 3M's clinical data analytics platform. Apache Hadoop was configured to provide distributed storage and scalable batch processing, forming the core data lake and serving as persistent staging for analytic workloads. Workflows combined Apache Hadoop with Apache Spark for in-memory processing, while standard language runtimes such as Python, R and Java were used for model development and SQL was used for data interrogation. Notebook environments including Jupyter Notebook supported exploratory analysis and iterative model building. Integrations explicitly reflected the team’s technical experiences, including Spark and developer tooling such as PyCharm and RStudio, with Git and Gerrit used for source control and code review to support reproducible model pipelines. The environment operated alongside cloud and hybrid analytics experiences cited by the lab, including AWS, Databricks, Google Cloud and BigQuery, enabling a mix of on-premises Hadoop storage and cloud compute or analytics engines for model training and batch scoring. Apache Hadoop served as the canonical Big Data Infrastructure layer that connected raw healthcare feeds to downstream clinical analytics and R&D consumption. Governance and operational practices centered on the Data Science Lab, with controlled data access, code review workflows using Git and Gerrit, and lifecycle handoff patterns for moving models from experimentation to production. Operational responsibilities included configuration management, job scheduling and packaging of models for deployment into 3M's clinical data analytics platform.
4INFO Professional services 100 $28M United States Apache Software Apache Hadoop Database Management 2010 n/a
In 2010, 4INFO implemented Apache Hadoop as Big Data Infrastructure to architect and build a new reporting infrastructure utilizing Hadoop and Hive, focused on delivering near real time reporting capabilities for the business. The deployment established a distributed data storage and processing foundation using Apache Hadoop as the core platform, with Apache Hive used as the SQL query layer to enable analyst-friendly reporting and ad hoc queries against large datasets. The implementation included configuration of storage and compute tiers, a metadata and query service through Hive, and the construction of ingestion pipelines for both batch and micro‑batch data flows to support low-latency reporting. Functional capabilities emphasized scalable HDFS-based storage, a query and analytics layer via Apache Hive, and pipeline orchestration and transformation logic to normalize data for downstream reports. Operational coverage targeted the reporting and analytics function across 4INFO, with governance workstreams for data schema management, access control and query governance to ensure consistent reporting. Apache Hadoop and Apache Hive were explicitly restated as the platform components enabling the Big Data Infrastructure, and the project outcome was to provide the business with near real time reporting capability through a centralized Hadoop-based reporting infrastructure.
Life Sciences 55000 $56.3B United States Apache Software Apache Hadoop Database Management 2014 n/a
Professional Services 13000 $7.5B United States Apache Software Apache Hadoop Database Management 2015 n/a
Professional Services 3650 $650M United States Apache Software Apache Hadoop Database Management 2017 n/a
Professional services 130 $15M United States Apache Software Apache Hadoop Database Management 2004 n/a
Media 569 $137M United States Apache Software Apache Hadoop Database Management 2015 n/a
Insurance 3500 $650M United States Apache Software Apache Hadoop Database Management 2013 n/a
Manufacturing 27900 $14.4B United States Apache Software Apache Hadoop Database Management 2014 n/a
Showing 1 to 10 of 311 entries

Buyer Intent: Companies Evaluating Apache Hadoop

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Apache Hadoop. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Apache Hadoop for Database Management include:

  1. Merck, a United States based Life Sciences organization with 73000 Employees
  2. Bexhill College United Kingdom, a United Kingdom based Education company with 150 Employees
  3. Horizon Forest Products, a United States based Distribution organization with 200 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

Logo Company Industry Employees Revenue Country Evaluated
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FAQ - APPS RUN THE WORLD Apache Hadoop Coverage

Apache Hadoop is a Database Management solution from Apache Software.

Companies worldwide use Apache Hadoop, from small firms to large enterprises across 21+ industries.

Organizations such as Walmart, Apple, United Healthcare, CVS Health and McKesson are recorded users of Apache Hadoop for Database Management.

Companies using Apache Hadoop are most concentrated in Retail, Manufacturing and Insurance, with adoption spanning over 21 industries.

Companies using Apache Hadoop are most concentrated in United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Apache Hadoop across Americas, EMEA, and APAC.

Companies using Apache Hadoop range from small businesses with 0-100 employees - 5.79%, to mid-sized firms with 101-1,000 employees - 19.61%, large organizations with 1,001-10,000 employees - 27.33%, and global enterprises with 10,000+ employees - 47.27%.

Customers of Apache Hadoop include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified Apache Hadoop customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Database Management.