KAFKA INTEGRATION AND STREAM PROCESSING

Take Apache Kafka to the Next Level

SCALABLE REAL-TIME INTEGRATION AND SQL-BASED STREAM PROCESSING FOR KAFKA

Apache Kafka has seen increasing adoption among enterprises of all sizes as a high-performance, fault-tolerant messaging system. To get the most value from your Kafka solutions you need to ingest data into Kafka, prepare it for different consumers, and distribute to a broad range of systems on-premises and in the cloud. Also, many Kafka users choose to analyze and visualize the data flowing through Kafka to gain timely intelligence. The Striim platform enables you to integrate, process, analyze, visualize, and deliver high-volumes of streaming data for your Kafka environments with an intuitive UI and SQL-based language for easy and fast development.

WHY STRIIM FOR KAFKA

Kafka Integration and Stream Processing

Striim completes Apache Kafka solutions by delivering high-performance real-time data integration with built-in SQL-based, in-memory stream processing, analytics, and data visualization in a single, patented platform.  Using its drag-and-drop UI, pre-built wizards for Kafka integration, and SQL-based development language, you can significantly accelerate Kafka integration and stream analytics application development.

Striim provides the key pieces of in-memory technology to enable enterprise-grade Kafka solutions with end-to-end security, recoverability, reliability (including exactly once processing), and scalability. Striim also ships with Kafka built-in so you can harness its capabilities without having to rely on coding.

EXPAND KAFKA'S REACH
EXPAND KAFKA'S REACH
Ingest streaming data from any relevant source, and deliver where needed on-premises or in the cloud
DELIVER IN THE RIGHT FORMAT
DELIVER IN THE RIGHT FORMAT
Transform, filter, aggregate, enrich streaming Kafka data without extensive coding
VIEW AND ANALYZE STREAMING DATA
VIEW AND ANALYZE STREAMING DATA
Gain real-time intelligence with alerts, and visualize data in Kafka without needing another product
Customer Use Case

LEADING CREDIT CARD NETWORK

To build a real-time security event hub supporting its cyber security analytics efforts, the leading credit card network decided to use Striim with Apache Kafka. Striim collects, prepares, and correlates all types of security data, and distributes to various targets. While publishing pre-processed events to the Kafka-based enterprise bus in JSON format, the Striim platform tracks and records key metrics about all the events collected, and performs analytics and file management where needed.

Striim also displays card management events coming from the website via real-time dashboards, and allows to run machine learning algorithms on this streaming data for improved customer experience.

Kafka Integration and Stream Processing


Gained a comprehensive and real-time view into all security events


Supports security analytics applications with real-time, pre-processed data

 


Delivers fast, accurate, and detailed information to incident handlers

How Striim Works

LOW- IMPACT REAL-TIME DATA INTEGRATION WITH BUILT-IN INTELLIGENCE

Striim ingests real-time data in to Kafka from a wide variety of sources including databases, log files, IoT devices, message queues, for different data types such as JSON, XML, delimited, binary, free text, change records. For transactional databases, it uses non-intrusive change data capture (CDC). Striim runs SQL-based continuous queries to filter, transform, aggregate, enrich, and analyze the data-in-motion before delivering it to virtually any target with sub-second latency. Striim offers multi-threaded delivery to Kafka with automated partitioning, and a broad range of metrics to monitor streaming data pipelines in real time.

Kafka Integration and Stream Processing


Continuous, Non-Intrusive, Real-Time Structured and Unstructured Data Ingestion and Delivery


In-Flight Data Filtering, Transformation, Aggregation, Enrichment, Analytics, and Visualization


High-Performance, Scalable, and Reliable In-Memory Processing with Real-Time Data Pipeline Monitoring

See how streaming data integration can work for you.

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