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Turn your data in motion into analytics in motion with Imply: the real-time analytics platform built from Apache Druid.

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Building on Apache Kafka and Druid

Apache Druid is designed for rapid ingestion and immediate querying of stream data. Whether you’re ingesting thousands or millions of events per second, Druid delivers exactly-once ingestion and subsecond latency for data streams without needing a Kafka connector. When existing databases and legacy analytics stacks fail to meet real-time requirements, Druid is the answer.

Learn more about the Kafka-to-Druid architecture

Druid Kafka

Get started with Confluent Cloud and Imply Polaris

Together, Imply Polaris and Confluent Cloud provide a complete, fully-managed, cloud-native data architecture for real-time analytics applications at any scale. Get the full power of Kafka and Druid without the production risk and infrastructure management, while accelerating time to value for real-time analytics use cases.

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Analyzing streaming data with Imply

Imply is purpose-built for stream ingestion. It ingests event-by-event, not a series of batched data files sent sequentially to mimic a stream. This means that Imply supports query-on-arrival. It’s true real-time analytics with no wait for data to be batched and then delivered.

Confluent and Imply
  • Event-based ingestion

    Unlike systems that rely on periodic batch processing, Druid’s event-based ingestion enables data to be ingested and processed as soon as events occur.

  • Query-on-arrival

    Druid provides instantaneous access to streaming data, enabling individuals and/or applications to query data as soon as it enters the stream.

  • High EPS scalability

    Druid handles data streams up to millions of events per second with ease, ideal for highly dynamic data.

  • Auto schema discovery

    Druid automatically discerns the fields and types of data ingested, updating tables to align with evolving data. 

  • Guaranteed consistency

    Druid guarantees data consistency—preventing duplicates or data loss—through its native indexing service.

  • Continuous backup

    Druid ensures no data loss of streaming data as it persists data segments to deep storage automatically.

Real-time analytics use cases

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