List of VictoriaMetrics Customers
San Francisco, 94101, CA,
United States
Since 2010, our global team of researchers has been studying VictoriaMetrics 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 VictoriaMetrics for Open-Source Database 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 VictoriaMetrics for Open-Source Database include: Grammarly, a United States based Professional Services organisation with 1000 employees and revenues of $250.0 million, Groove X, a Japan based Manufacturing organisation with 121 employees and revenues of $56.0 million, Sensedia Brazil, a Brazil based Professional Services organisation with 450 employees and revenues of $36.0 million and many others.
Contact us if you need a completed and verified list of companies using VictoriaMetrics, 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 VictoriaMetrics 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 | Insight Source |
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Grammarly | Professional Services | 1000 | $250M | United States | VictoriaMetrics | VictoriaMetrics | Open-Source Database | 2019 | n/a | In 2019, Grammarly implemented VictoriaMetrics as its Open-Source Database to serve large-scale observability and metrics needs in the United States. The deployment positioned VictoriaMetrics as a Prometheus and OpenMetrics compatible time series backend, centralizing metric ingestion and long term storage to support monitoring, dashboards and alerting across engineering and site reliability teams. The architecture relied on VictoriaMetrics nodes to ingest OpenMetrics-format streams and provide a compact time series store and query layer optimized for high ingestion rates and low-latency queries. Integrations focused on Prometheus compatible scraping and existing monitoring pipelines, with a phased rollout to instrument services and onboard alerting and dashboard consumers. Grammarly reported roughly 10× lower costs and improved ingestion and query performance following the VictoriaMetrics implementation. | |
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Groove X | Manufacturing | 121 | $56M | Japan | VictoriaMetrics | VictoriaMetrics | Open-Source Database | 2021 | n/a | In 2021, Groove X implemented VictoriaMetrics to support device health monitoring for robots and charging stations in Tokyo, Japan. VictoriaMetrics was provisioned as the central Open-Source Database for the company observability layer, with the objective of reducing latency and improving metrics correctness and maintainability. The deployment centered on VictoriaMetrics as Prometheus compatible time series storage paired with Grafana for visualization and dashboarding. Configuration emphasized high ingestion throughput, efficient time series indexing and compression, and Prometheus compatible query endpoints to accept telemetry scraped from device agents. Operational coverage included device telemetry for robotics and charging infrastructure across Groove X sites in Tokyo, serving manufacturing operations and maintenance teams. The vendor case study reports better performance and scalability for their observability stack, and implementation outcomes cited reduced latency and improved metrics correctness and maintainability. | |
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Sensedia Brazil | Professional Services | 450 | $36M | Brazil | VictoriaMetrics | VictoriaMetrics | Open-Source Database | 2020 | n/a | In 2020, Sensedia Brazil deployed VictoriaMetrics, an Open-Source Database, to store Prometheus-compatible metrics for its API platform in Brazil and moved the solution into production days before Black Friday 2020 to secure scalability and high availability. The implementation positioned VictoriaMetrics as the primary metrics storage layer for API observability across Sensedia Brazil, supporting PromQL query compatibility and Grafana visualization workflows. Deployment into production was executed under a tight timeline to meet peak traffic demands immediately ahead of a major retail event. The implementation focused on PromQL and Grafana-compatible metrics storage capabilities, configuring VictoriaMetrics for high-throughput ingestion and compressed time series retention consistent with Prometheus remote write semantics. Modules and functional capabilities inferred from the deployment include a PromQL query engine, native support for Prometheus-compatible ingestion, and storage optimization for high-cardinality API metrics. Configuration emphasized sustained ingestion performance and query responsiveness for dashboards and alerting. Integration points included Prometheus-compatible collectors and Grafana for visualization, enabling end-to-end metric collection, storage, and dashboarding for Sensedia Brazil’s API engineering and operations teams. Operational scope covered production monitoring of the API platform in Brazil with an accelerated rollout schedule tied to Black Friday 2020, and governance centered on stabilizing the metrics pipeline during peak traffic windows. Sensedia Brazil reported reduced resource usage while handling record metric generation during peak traffic, with the deployment delivering a scalable Open-Source Database foundation for ongoing API observability. |
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