Hive.co builds marketing automation software for event promoters, anchored to ticketing data. The tech stack reveals a data-infrastructure-heavy operation: Kubernetes, Docker, Kinesis, PySpark, ClickHouse, Snowflake, and dbt underpin high-volume ingestion and real-time pipelines. Active projects span agentic AI, Ticketmaster API integration, and a personalized email/SMS pipeline—while pain points cluster around scaling data throughput, query performance, and production datastore capacity, suggesting the product is hitting infrastructure limits as customer volume grows.
Hive.co is a SaaS marketing platform designed for event promoters to build revenue-driving campaigns powered by ticketing data. The platform connects to event ticketing systems, processes attendee and sales data, and enables email, SMS, and paid-ad campaigns (via Meta and Shopify integrations). Founded in 2014 and based in Kitchener, Ontario, the company operates with roughly 50–200 employees across sales, engineering, product, support, and data functions. The current hiring focus skews sales-led (9 open roles) with concurrent engineering investment (7 roles), indicating both customer acquisition and product scaling in parallel.
Kubernetes, Docker, AWS (RDS, Kinesis, Glue, Lambda), PySpark, ClickHouse, MongoDB, Elasticsearch, Django, React, Salesforce, Snowflake, dbt, Datadog, and Sentry. The stack emphasizes data pipelines and real-time event processing.
Active projects include agentic AI capabilities, Kubernetes/Docker task processing, Ticketmaster API integration, personalized email/SMS pipelines, and monitoring/observability implementation—alongside GTM playbook and customer onboarding improvements.
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