List of Google Cloud Dataflow Customers
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Since 2010, our global team of researchers has been studying Google Cloud Dataflow customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Google Cloud Dataflow for Application Hosting and Computing Services from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Google Cloud Dataflow for Application Hosting and Computing Services include: Hackensack Meridian Health, a United States based Healthcare organisation with 36000 employees and revenues of $8.00 billion, Lightricks, a Israel based Professional Services organisation with 650 employees and revenues of $150.0 million, Glean, a United States based Professional Services organisation with 200 employees and revenues of $32.0 million and many others.
Contact us if you need a completed and verified list of companies using Google Cloud Dataflow, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Glean | Professional Services | 200 | $32M | United States | Google Cloud Dataflow | Application Hosting and Computing Services | 2020 | n/a |
In 2020, Glean implemented Google Cloud Dataflow as a core component of its Application Hosting and Computing Services layer to process workplace knowledge at scale. Google Cloud Dataflow is used to extract relevant pieces from content indexed from multiple internal sources and to augment that content with relevance signals before committing records to the search index hosted in the projects Google Kubernetes Engine.
The implementation centers on data processing pipelines that perform extraction, transformation, and relevance signal augmentation, and it also includes pipeline stages dedicated to generating training data at scale for models that are trained on Google Cloud. Google Cloud Dataflow pipelines are architected to support complex and flexible transformations, enabling batch and streaming style ingestion patterns consistent with enterprise search indexing and model training data preparation.
Operationally the Dataflow implementation integrates directly with the Google Kubernetes Engine hosted search index and with model training workloads running on Google Cloud, providing a continuous feed of indexed documents and curated training sets. Pipelines handle large corpuses of internal content sourced from disparate workplace systems, centralizing preprocessing and feature enrichment in the cloud compute layer.
Governance for the deployment is implemented within Gleans Google Cloud project, with Dataflow acting as the orchestration and autoscaling execution fabric for ETL and training data generation tasks. As a result, Google Cloud Dataflow enables Glean to build complex, flexible data processing pipelines that autoscale efficiently when processing large corpuses of data, while serving both search indexing and model training functions.
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Hackensack Meridian Health | Healthcare | 36000 | $8.0B | United States | Google Cloud Dataflow | Application Hosting and Computing Services | 2023 | n/a |
In 2023 Hackensack Meridian Health implemented Google Cloud Dataflow as part of its cloud and data modernization within Application Hosting and Computing Services, moving its first non-production EHR Playground workload to Google Cloud. The initial deployment targets data processing and orchestration for EHR workloads, supporting clinical education use cases while establishing a foundation for analytics and AI-driven services.
The Google Cloud Dataflow implementation centers on pipeline orchestration, batch and streaming data processing, and automated ingestion of EHR Playground activity to enable training, testing, and analytics workflows. Functional capabilities implemented include data transformation, event and transaction processing for simulated orders and clinical notes, and pipeline automation to support onboarding of residents and nursing students without using real patient data.
Integrations described in the announcement align the Google Cloud Dataflow deployment with Google Cloud AI and machine learning offerings, Google Cloud secure storage, and broader productivity and analytics tooling already in the partnership. The program is scoped to expand over the next three years to bring additional EHR workloads and significant data sources into the cloud environment, enabling cross-source analysis and the development of predictive models and generative AI use cases.
Governance and privacy controls were emphasized in the rollout, with Google Cloud data governance and privacy policies used to allow the customer to retain control over data, and platform capabilities configured to support HIPAA related controls, model output monitoring, safety guardrails, and model documentation. Early outcomes cited by the organization include increased agility, improved reliability, and increased security, while the cloud architecture and Google Cloud Dataflow pipelines are positioned to accelerate future analytics and AI deployments across clinical and operational functions.
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Lightricks | Professional Services | 650 | $150M | Israel | Google Cloud Dataflow | Application Hosting and Computing Services | 2022 | DoiT International |
In 2022, Lightricks deployed Google Cloud Dataflow as part of a broader Google Cloud implementation categorized under Application Hosting and Computing Services, using Dataflow together with BigQuery to support high throughput analytics and streaming ingestion. The implementation is explicitly positioned to serve business intelligence, data science, developers, and product teams, and to handle the mobile user behavior telemetry that drives product optimization and recommendation engines.
The technical implementation centered on Google Cloud Dataflow pipelines that automate the ingest and analysis of thousands of events per second, enabling ingestion rates reported at around 10,000 events per second or roughly a billion events per day. BigQuery was used to separate storage from compute, allowing scheduled queries to be prepared minutes before events are registered and making compute resources available on demand. Containerized infrastructure was established on Google Kubernetes Engine in a matter of weeks, and machine learning workloads ran on Compute Engine while a staged migration to Vertex AI was underway to move models to managed services for faster scaling.
Integrations were implemented with BigQuery, Google Kubernetes Engine, Compute Engine, Vertex AI, and external services including Cloudinary and Elasticsearch, with secure traffic forwarding mechanisms that avoid exposure to the public Internet. Lightricks worked with DoiT International on architecture and operational support, including synchronizing on-premises compute and research data lakes with cloud clusters to support model training and inference. Operational coverage included marketing analytics, product optimization, recommendation engine teams, and centralized data platform functions.
The rollout emphasized operational simplicity and governance, reducing infrastructure maintenance overhead so a small engineering and DevOps team could provision clusters and pipelines rapidly. Autoscale in Dataflow removed previous ingestion limits and prevented data blocking, while GKE reduced cluster configuration and upgrade effort and was cited as cost effective for Lightricks workloads. The implementation is described as enabling large scale event processing and machine learning experimentation without inhibiting user experience, and as supporting planned 2022 backend initiatives such as shared profiles and media upload services.
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FAQ - APPS RUN THE WORLD Google Cloud Dataflow Coverage
Google Cloud Dataflow is a Application Hosting and Computing Services solution from Google.
Companies worldwide use Google Cloud Dataflow, from small firms to large enterprises across 21+ industries.
Organizations such as Hackensack Meridian Health, Lightricks and Glean are recorded users of
Google Cloud Dataflow for Application Hosting and Computing Services.
Companies using Google Cloud Dataflow are most concentrated in Healthcare and Professional Services, with adoption spanning over 21 industries.
Companies using Google Cloud Dataflow are most concentrated in United States and Israel, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Google Cloud Dataflow across Americas, EMEA, and APAC.
Companies using Google Cloud Dataflow range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 66.67%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 33.33%.
Customers of Google Cloud Dataflow 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 Google Cloud Dataflow customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Application Hosting and Computing Services.