STRIIM BLOG

Take Apache Kafka to the Next Level

Ryan Siss
March 12, 2018 · 3 minute read

Apache Kafka has become the de facto standard for providing a unified, high-throughput, low-latency platform for handling real-time data feeds.  With a Kafka-based infrastructure in place, it’s time to take Kafka to the next level. Join us on Thursday, March 15, at 11am PT or 2pm ET for a half-hour discussion on the top 5 reasons to up the ante on your Kafka implementation.

Reason #1: Continuous Ingestion into Kafka

While Apache Kafka is gaining great traction as a fault-tolerant, high-speed open source messaging solution, the value users gain is limited to the data sources they can feed into Kafka in a streaming fashion.

Join this 30-minute webinar to see how easy it can be to use pre-built wizards to ingest and integrate data into Kafka from a wide variety of sources including:

  • Databases via non-intrusive change data capture (ie, Oracle, MS SQL, MySQL, HPE NonStop, Maria DB)
  • Files (ie, log files, system files, batch files)
  • Big Data (ie, HDFS, Hbase, Hive)
  • Messaging (ie, Kafka, Flume, JMS, AMQP)
  • Cloud (ie, Amazon S3, AWS RDS, Salesforce)
  • Network
  • Sensors and IoT Devices

Reason #2: SQL-Based Stream Processing on Kafka

Over the past 6 months, a lot has been written about how the future of Apache Kafka will incorporate stream processing.

The future is now. Striim has been providing enterprise-grade, SQL-based stream processing for Kafka for 2 years in large and business-critical environments worldwide.

Join this webinar to learn how easy it can be to provide SQL-based Kafka stream processing, as well as for other data pipelines, with capabilities including:

  • Filtering
  • Masking
  • Aggregation
  • Transformations
  • Enrichment with dynamically changing data
  • Time Windowing

Reason #3: Making Apache Kafka Applications Enterprise-Grade

Chances are, you are using Apache Kafka for messaging, but not for building analytics applications. Why? If you’re like many companies, the open source stream processing solutions around Kafka simply don’t hold up in production.

Striim’s patented technology is widely used for enterprise-grade, SQL-based stream processing for Kafka, and delivers complex streaming integration and analytics for one of the largest Kafka implementations in the world.

Join this 30-minute webinar to learn how you can build next-generation Kafka-based analytics applications with built-in HA, scalability, recovery, failover, security and exactly-once processing guarantees.

Reason #4: Kafka Integration via Streaming

Apache Kafka is neither a source, nor a destination. To truly leverage Kafka, it is necessary to integrate both from streaming data sources into Kafka, and from Kafka to a variety of targets, in a streaming fashion in real time.

Striim’s patented technology is able to continuously collect data from a wide variety of sources (such as enterprise databases via log-based change data capture, log files and sensors) and move that data in real time onto a Kafka queue. In addition, Striim can continuously collect data from Kafka and move it in real time to targets including a broad range of Big Data, database environments, on-premises or in the Cloud.

Join this 30-minute webinar to learn how you can easily integrate your Kafka solution with a broad range of streaming data sources and enterprise targets.

Reason #5: Kafka Visualization via Real-Time Dashboards

Sometimes, all you need is visibility.

With Striim, you can continuously visualize data flowing in a Kafka environment via real-time, push-based dashboards. To get even more value, you can easily perform SQL-based processing of the data in-motion and provide the best possible views into your streaming data.

Join us to learn how easy it can be to incorporate stream processing and real-time visualizations into your Kafka solutions.

Take Kafka to the Next Level
Streaming Integration and SQL-Based Stream Processing for Apache Kafka Environments
March 15, 2018
11:00 – 11:30am PT / 2:00 – 2:30pm ET
Register Today!

See how streaming data integration can work for you.

Schedule a Demo Download