Used by over 80% of Fortune 100 companies including LinkedIn, Netflix, Uber, and Goldman Sachs, Apache Kafka processes trillions of messages per day as the world's most widely deployed distributed event streaming platform. Since version 4.0 released in March 2025, Kafka operates exclusively with KRaft consensus, replacing Apache ZooKeeper entirely with an internal Raft-based metadata quorum managed by controller nodes, reducing operational complexity and eliminating external coordination dependencies. Topics are organized as append-only partitioned commit logs with configurable replication factors across brokers, delivering network-limited throughput with end-to-end latencies as low as 2 milliseconds. Kafka Streams provides a client library for building stateful stream processing applications with exactly-once semantics, windowed aggregations, joins across streams and tables, and interactive queries against local state stores. Kafka Connect integrates with hundreds of systems including PostgreSQL, MySQL, Elasticsearch, Amazon S3, MongoDB, HDFS, and JMS through a standardized connector framework with distributed worker mode and automatic offset management. Share Groups introduced in version 4.2 deliver queue-style consumption semantics alongside traditional consumer groups, enabling Kafka to serve both pub-sub and point-to-point messaging patterns natively. The Schema Registry enforces Avro, Protobuf, and JSON Schema compatibility rules across producers and consumers, preventing schema evolution from breaking downstream applications. Tiered Storage offloads older log segments to object storage like S3 while maintaining transparent consumer access, dramatically reducing local broker storage costs for long-retention topics. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Deployed at thousands of enterprises across financial services, healthcare, government, and telecommunications, Apache NiFi is the industry-standard platform for building automated data pipelines through a visual drag-and-drop browser interface that requires zero coding for common integration patterns. The flow-based programming model connects over 300 built-in processors covering relational databases via ExecuteSQL and PutDatabaseRecord, Apache Kafka with PublishKafka and ConsumeKafka, HTTP endpoints through InvokeHTTP and ListenHTTP, cloud storage for AWS S3, Azure Blob, and Google Cloud Storage, SFTP/FTP file transfers, and JSON, XML, CSV, and Avro transformations. Data provenance tracking logs every routing decision, transformation, and delivery for every FlowFile, creating a searchable lineage graph from source to destination with full content replay capability for auditing and debugging. Guaranteed delivery uses configurable backpressure thresholds, prioritized queuing with latency or throughput optimization, and automatic retry with exponential backoff, ensuring no data loss even during downstream outages. The zero-leader clustering architecture distributes processing across nodes with automatic load balancing, while site-to-site protocol enables secure data transfer between NiFi instances across network boundaries. Security includes OpenID Connect and SAML 2.0 single sign-on, role-based access control with fine-grained policies per component, and TLS encryption for all communication. Custom processors can be written in Java and packaged as NAR bundles, or implemented directly in Python through the native scripting framework. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.