Enterprise data lives in complex ecosystems—SAP, Oracle, Salesforce, ServiceNow, IBM Mainframes, and more. This article explores how Confluent and Databricks…
Confluent and Databricks enable a modern data architecture that unifies real-time streaming and lakehouse analytics. By combining shift-left principles with…
This blog explores how Confluent and Databricks address data integration and processing in modern architectures. Confluent provides real-time, event-driven pipelines…
Batch processing introduces delays, complexity, and data quality issues that modern businesses can no longer afford. This article outlines the…
Discover when Apache Flink is the right tool for your stream processing needs. Explore its role in stateful and stateless…
An open table format framework like Apache Iceberg is essential in the enterprise architecture to ensure reliable data management and…
Data integration is a hard challenge in every enterprise. Batch processing and Reverse ETL are common practices in a data…
Snowflake is a leading cloud-native data warehouse. Integration patterns include batch data integration, Zero ETL and near real-time data ingestion…
This blog post explores the state of data streaming for the healthcare industry powered by Apache Kafka and Apache Flink.…
Aviation and travel are notoriously vulnerable to social, economic, and political events, as well as the ever-changing expectations of consumers.…