Cloudera SQL Stream Builder is a comprehensive interactive UI for creating stateful stream processing jobs using SQL which gets converted into optimized Flink jobs. By using SQL, you can simply and easily declare expressions that filter, aggregate, route, and otherwise mutate streams of data. SQL Stream Builder is a job management interface that you can use to compose and run SQL on streams as well as to create durable data APIs for the results.

Ensure that data is processed exactly once at all times even during errors and retries. For example, a financial services company needs to use stream processing to coordinate hundreds of back-office transactions systems when consumers pay their home mortgage.

Detect and deal with streaming events that come out of order. For example, real-time fraudulent services need to ensure data is processed in the right order even if data arrives late.

Achieve in-memory, one-at-a time stream processing performance. For example, process requests of 30 million active users making credit card payments, transfers, and balance lookups with millisecond latency.

Trigger events when dealing with hundreds of streaming sources and millions of events per second per stream. For example, when a patient checks into the ER, the system reaches out to external systems to pull patient-specific data from hundreds of sources so it’s available in an EMR by the time the patient arrives in the exam room.

Streaming data has little value unless it can easily integrate, join, and mesh those streams with other at-rest data sources including warehouses, relational databases, and data lakes. Configure data providers using out-of-the-box connectors or your own connector to any data source. Once the data providers are created, the user can easily create virtual tables using DDL. Complex integration between multiple streams and batch data sources becomes easier with well-known SQL constructs such as joins and aggregations.

Supports millions of messages per second with low latency and high throughput, scaling elastically and transparently without downtime. Addresses a wide range of streaming data initiatives, enabling enterprises to keep up with customer demand, provide better services, and proactively manage risk.

Streams Messaging Manager provides a single pane of glass view with end-to-end visibility into how data moves across Kafka clusters—among producers, brokers, topics, and consumers—allowing you to track data lineage and governance from edge to cloud. It also simplifies troubleshooting of Kafka environments with intelligent filtering and sorting.

Streams Replication Manager, based on Mirrormaker 2, offers fault-tolerant, scalable, and robust cross-cluster Kafka topic replication, as well as replication monitoring and metrics at the cluster and topic levels. Delivers high availability, disaster recovery, cloud migrations, geo-proximity, and many others.

Schema Registry lets you manage, share, and support the evolution of all producer and customer schemas in a shared schema repository that allows applications to flexibly interact with each other across the Kafka landscape. Safely mitigate interruptions that occur due to schema mismatches.

Cruise Control lets you manage and load-balance large Kafka installations, as well as automatically detect and remediate anomalies. Address hard problems such as frequent hardware/virtual machine failures, cluster expansion/reduction, and load skew among brokers.

Cloudera SDX offers centralized security, control policies, governance, and data lineage across all components. They are set once and automatically enforced and are vendor-agnostic, allowing you to confidently embrace multi-cloud and hybrid cloud strategies. Supports the four main pillars of security: Identity, access, data protection, and visibility.