List of Apache Samza Customers
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Since 2010, our global team of researchers has been studying Apache Samza 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 Apache Samza for Apps Development 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 Apache Samza for Apps Development include: Slack, a United States based Communications organisation with 2700 employees and revenues of $903.0 million, Optimizely, a United States based Professional Services organisation with 1500 employees and revenues of $400.0 million and many others.
Contact us if you need a completed and verified list of companies using Apache Samza, 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 Apache Samza 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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Optimizely | Professional Services | 1500 | $400M | United States | Apache Software | Apache Samza | Apps Development | 2016 | n/a |
In 2016, Optimizely implemented Apache Samza to compute real time session metrics and perform event ingestion for its experimentation and personalization platform in the United States. This deployment is categorized as Apps Development and addresses analytics and product metrics use cases within the company.
The Apache Samza implementation was used to build streaming processing pipelines that perform sessionization and on the fly aggregation of events, feeding downstream analytics and personalization services. Configuration focused on continuous event ingestion, stateful stream processing and low latency query paths in support of product metrics and experimentation workloads.
Operational coverage included product analytics, experimentation and personalization teams, with integrations to HBase as a storage and serving layer. Optimizely documented impacts on storage and write patterns to HBase as part of the deployment, reflecting tighter coupling between streaming processors and columnar storage for serving session level metrics.
Optimizely reported median query latency reductions from above 40 ms to approximately 5 ms, along with lower HBase write rate and reduced storage requirements after the Apache Samza deployment.
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Slack | Communications | 2700 | $903M | United States | Apache Software | Apache Samza | Apps Development | 2017 | n/a |
In 2017, Slack deployed Apache Samza to build streaming data pipelines for infrastructure monitoring, alerting and experimentation analytics in the United States. This implementation uses Apache Samza within the Apps Category .
The Apache Samza implementation instruments pipelines that process billions of log and metric events through routers, processors and converters. These pipeline stages implement high throughput stream ingestion, event routing and data conversion to enable near real time alerting and observability for Slack services.
Operational scope centers on operations and monitoring, with the implementation supporting infrastructure monitoring, alerting workflows and experimentation analytics across Slack engineering and site reliability functions in the United States. The pipelines feed observability and alerting consumers and are structured for continuous streaming processing rather than batch aggregation.
The available case study does not specify exact project start dates, therefore the referenced year is an estimate. The narrative emphasizes Apache Samza pipeline architecture, streaming modules, event routing and conversion components as the primary implementation signals.
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