Organizations Tagged with ingestion-pipeline: Data Ingestion, Real-Time ETL, and Scalable Pipeline Architectures
Explore organizations that are tagged with ingestion-pipeline and discover how they implement data ingestion and real-time ETL pipelines for analytics, machine learning, and operational systems using technologies like Kafka, Kinesis, Flink, Spark Structured Streaming, Debezium (CDC), and batch ingestion patterns. This curated list of organizations (filtered by the tags pillar) highlights implementation patterns, schema evolution strategies, data validation and observability practices, throughput and latency tradeoffs, and cloud-agnostic deployment models—use the filtering UI to narrow results by data source, tooling, latency requirements, or scalability targets. Click to compare organization profiles, implementation case studies, open-source repositories, architectural diagrams, and operational best practices to find the right ingestion-pipeline approaches and accelerate integration or collaboration.
