List of Elastic Beats Customers
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Since 2010, our global team of researchers has been studying Elastic Beats 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 Elastic Beats for Analytics and BI, Data Warehouse 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 Elastic Beats for Analytics and BI, Data Warehouse include: Goldman Sachs, a United States based Banking and Financial Services organisation with 48300 employees and revenues of $53.51 billion, eBay, a United States based Retail organisation with 11500 employees and revenues of $2.60 billion, Gourmet Navigatororporated, a Japan based Communications organisation with 1334 employees and revenues of $400.0 million and many others.
Contact us if you need a completed and verified list of companies using Elastic Beats, 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.
The Elastic Beats 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 software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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eBay | Retail | 11500 | $2.6B | United States | Elasticsearch | Elastic Beats | Analytics and BI,Data Warehouse | 2017 | n/a |
In 2017, eBay implemented Elastic Beats for Analytics and BI,Data Warehouse to capture containerized logs and metrics across its infrastructure. The deployment centered on using vendor Elasticsearch's Elastic Stack as the central analytics and observability platform.
Filebeat and Metricbeat were deployed to collect and ship logs and metrics from Docker and Kubernetes nodes, instrumenting application logs and host and container metrics. The team built custom Collectbeat and autodiscover processors to tag and enrich event and metric streams for analytics, enabling consistent metadata insertion at source.
Beats agents ran adjacent to container workloads and fed data into a centralized Elastic Stack cluster, supporting large-scale observability and analytics for eBay's IT and observability functions in the United States. Elastic Beats served as the edge ingestion layer, with Filebeat and Metricbeat functioning as the primary modules for log and metric collection.
Operational governance emphasized collection-time tagging and enrichment and documented usage patterns in Elastic's eBay customer story, which explicitly references Filebeat and Metricbeat. Elastic Beats became the standardized ingestion mechanism for container telemetry, aligning collection workflows with analytics and monitoring teams.
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Goldman Sachs | Banking and Financial Services | 48300 | $53.5B | United States | Elasticsearch | Elastic Beats | Analytics and BI,Data Warehouse | 2015 | n/a |
In 2015 Goldman Sachs implemented Elastic Beats as part of an Elastic Stack deployment to support Analytics and BI,Data Warehouse use cases. The implementation centralized Elasticsearch usage to track trade flows and enable real time analytics across multiple trading and finance systems in the United States.
The deployment used Elastic Beats as lightweight data shippers to capture logs and streamed events from trading infrastructure, feeding ingestion pipelines that indexed into Elasticsearch for search and analytics. Configuration focused on event forwarding, structured indexing, and downstream dashboarding and alerting to surface trade flow telemetry for operational teams.
Operational scope included trading desks and finance operations where trade flow visibility and event level tracing were priorities, with Beats agents standardizing log and event collection across heterogeneous systems. Integrations touched multiple internal trading and finance systems to consolidate event streams into a centralized search and analytics layer.
Governance centered on centralizing Elasticsearch usage and standardizing collection and indexing practices to improve operational visibility and situational awareness for trade monitoring. Elastic Beats was positioned as the lightweight ingestion layer within the Elastic Stack to provide consistent event capture for analytics, search, and monitoring workflows.
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Gourmet Navigatororporated | Communications | 1334 | $400M | Japan | Elasticsearch | Elastic Beats | Analytics and BI,Data Warehouse | 2016 | n/a |
In 2016, Gourmet Navigatororporated implemented Elastic Beats as part of a broader Elastic Stack deployment to centralize log analytics and accelerate incident response for its platform in Japan. The Elastic Beats deployment was positioned in the Analytics and BI,Data Warehouse category to support operational monitoring and troubleshooting for IT and operations teams across the company.
The implementation used Elastic Beats for lightweight, agent based log and metric collection feeding into Elasticsearch for indexing and Kibana for visualization, reflecting the Elastic Stack architecture referenced by the vendor. Beats modules were inferred for multi source ingestion while Elasticsearch and Kibana provided the core indexing and dashboarding capabilities, aligning with standard data pipeline and log analytics workflows in this category.
Operational coverage focused on platform operations and IT monitoring across Japan, consolidating distributed logs into a central ingestion pipeline and index to enable real time dashboards and search driven troubleshooting. The deployment oriented data flows around centralized event capture and time series indexing, supporting both operational alerts and ad hoc investigation by operations teams.
Governance centered on centralizing log analytics to create shared visibility and consistent event semantics across applications, enabling strategic data reuse for cross application troubleshooting and monitoring. The project explicitly aimed to speed incident response and improve troubleshooting and operational monitoring, enabling IT and operations to move from siloed logs to a searchable, instrumented platform for incident investigation and operational analytics.
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