Streaming Data Ingest with Kafka
Enable real-time analytics with live data, from many sources, at scale
Apache Kafka enables big data analytics opportunities by providing a high-scale, low-latency platform for ingesting and processing live data streams. And with valuable data being managed in a variety of databases, enterprises can benefit from ingesting that data through Kafka to support their analytic or Data Lake initiatives. Doing so can be challenging due to potential impact on source systems, complexity in custom development, and ability to efficiently scale to support a large number of data sources. Attunity can help with its enterprise class change data capture (CDC) and data ingest software.
Attunity Replicate provides efficient, real-time, and scalable data ingest from many source database systems leveraging low-impact CDC technology. With Attunity Replicate, IT organizations gain:
- Real-time data capture. Feed live database changes to Kafka message brokers with low latency
- Support for many data sources. A single platform that supports many types of sources including all major RDBMS, data warehouses, and mainframe systems.
- Low Impact. Log-based CDC reduces the impact and a unique zero-footprint architecture eliminates the need to install any agents on source database systems
- Simplicity – no coding. Use an intuitive and configurable GUI to quickly and easily set up data feeds with no manual coding
- High Scale. An architecture and software that scales to ingest data from hundreds and thousands of databases, providing centralized monitoring and management capabilities
Attunity Replicate for Kafka
“The global rate of Kafka adoption is skyrocketing as enterprises embrace stream processing for big data. Attunity is an important partner for both Confluent and the broader Kafka community. Their technology simplifies integration with Kafka, enabling customers to more quickly derive greater business value from their data with less effort.”
Jabari Norton, VP Business Development at Confluent, the company founded by the creators of Apache Kafka.