List of IBM Analytics for Apache Spark (Managed Cloud Spark Service) Customers
Armonk, 10504, NY,
United States
Since 2010, our global team of researchers has been studying IBM Analytics for Apache Spark (Managed Cloud Spark Service) 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 IBM Analytics for Apache Spark (Managed Cloud Spark Service) for ML and Data Science Platforms 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 IBM Analytics for Apache Spark (Managed Cloud Spark Service) for ML and Data Science Platforms include: Merlin International, a United States based Professional Services organisation with 200 employees and revenues of $20.0 million, GreenCom, a Germany based Professional Services organisation with 50 employees and revenues of $10.0 million, Cloud-Nanny, a Netherlands based Professional Services organisation with 6 employees and revenues of $1.0 million and many others.
Contact us if you need a completed and verified list of companies using IBM Analytics for Apache Spark (Managed Cloud Spark Service), 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 Machine Learning software purchases.
The IBM Analytics for Apache Spark (Managed Cloud Spark Service) customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of Machine Learning software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
Cloud-Nanny | Professional Services | 6 | $1M | Netherlands | IBM | IBM Analytics for Apache Spark (Managed Cloud Spark Service) | ML and Data Science Platforms | 2016 | n/a |
In 2016, Cloud-Nanny deployed IBM Analytics for Apache Spark (Managed Cloud Spark Service) as the core of its ML and Data Science Platforms implementation for real time website classification and decisioning. The project targeted sub 40 microsecond lookups to decide whether to allow or block hundreds of thousands of web requests, emphasizing ultra low latency inference in a consumer facing parental control service.
Cloud-Nanny used IBM Analytics for Apache Spark (Managed Cloud Spark Service) to train and maintain a website classifier on a managed Spark cluster, producing categorical labels such as gaming, video, and adult content. The classifier is applied when a site is not already present in the curated database, and the inference output is compared against per family profiles to determine allow or block, or to escalate to a parental decision.
The implementation combined IBM dashDB as a managed cloud database for rapid blacklist and whitelist lookups with the managed Spark service for model training and online classification, all provisioned on IBM Bluemix to accelerate development and operations. Lookup latency and inference orchestration were engineered to minimize impact on the end user browsing experience, and parental decisions captured during escalations are fed back into the model training pipeline to support continuous learning.
Cloud-Nanny took the solution from proof of concept to production in 14 months, noting that building on Bluemix materially accelerated time to market, an estimated 50 percent faster than the company experienced with previous infrastructure setup. Operational governance centers on per family policy profiles and an interactive escalation workflow for human review, while iterative model retraining on the managed Spark cluster enables the classifier to adapt over time.
|
 |
GreenCom | Professional Services | 50 | $10M | Germany | IBM | IBM Analytics for Apache Spark (Managed Cloud Spark Service) | ML and Data Science Platforms | 2016 | n/a |
In 2016, GreenCom implemented IBM Analytics for Apache Spark (Managed Cloud Spark Service) as its primary ML and Data Science Platforms capability to support streaming analytics on its cloud-based data streams. GreenCom is a Germany-based professional services firm with 50 employees, and the company already uses Apache Spark to analyze data as it streams into the cloud platform while working closely with IBM to integrate with IBM Cloud and SoftLayer.
The deployment leverages the managed cloud Spark service to provision Spark clusters and centralize in-memory processing for both real-time and micro-batch data science workflows. IBM Analytics for Apache Spark (Managed Cloud Spark Service) was configured to support streaming analytics, distributed model development and training, and interactive exploratory analysis, aligning core ML and Data Science Platforms functionality such as distributed processing, iterative model scoring, and notebook-driven experimentation.
Integrations explicitly include IBM Cloud and SoftLayer for compute and storage orchestration, and the implementation ingests telemetry and event streams into the Spark-based pipeline. Operational scope focuses on data engineering, analytics and product engineering teams at GreenCom, with governance coordinated through close collaboration with IBM and a phased expansion of Spark usage as IBM continues to invest in the open source Spark project.
|
 |
Merlin International | Professional Services | 200 | $20M | United States | IBM | IBM Analytics for Apache Spark (Managed Cloud Spark Service) | ML and Data Science Platforms | 2017 | n/a |
In 2017 Merlin International implemented IBM Analytics for Apache Spark (Managed Cloud Spark Service) as the core compute layer for its analytics platform, aligning the deployment with the ML and Data Science Platforms category. The implementation establishes IBM Analytics for Apache Spark (Managed Cloud Spark Service) as a managed cloud compute service for distributed in-memory processing and model training across the organization.
The architecture combines the managed Spark service with an open source data stack to preserve adaptability to customer requirements. Apache Kafka is used for real-time streaming ingestion, Apache Cassandra and MongoDB serve as NoSQL storage tiers, and Apache Solr provides indexed search capabilities. Pivotal Spring Boot is implemented for backend microservice APIs and ReactJS Redux is used for frontend application state management, creating a layered pipeline from ingestion to presentation.
Operational coverage centers on Merlin International s analytics, data engineering and data science workflows within the Professional Services firm, supporting batch and streaming data processing and analytics-driven project delivery. Governance emphasis on remaining open source guided component selection and modular integration patterns, enabling the managed Spark service to interoperate with the selected messaging, storage and search systems without proprietary lock-in.
The implementation positions IBM Analytics for Apache Spark (Managed Cloud Spark Service) as the centralized compute orchestration point, integrating with Apache Kafka, Apache Cassandra, Apache Solr, MongoDB, Pivotal Spring Boot and ReactJS Redux to form a cohesive ML and data science platform for Merlin International.
|
Buyer Intent: Companies Evaluating IBM Analytics for Apache Spark (Managed Cloud Spark Service)
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||