Data Engineering

Deploying Debezium on AWS ECS or Fargate

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Debezium’s change data capture capabilities transform databases into event streams, enabling real-time data pipelines, microservices synchronization, and event-driven architectures. While Kafka Connect provides the standard deployment model for Debezium connectors, running this infrastructure on AWS demands careful consideration of container orchestration options. ECS (Elastic Container Service) and Fargate offer distinct approaches to deploying Debezium—ECS provides … Read more

Integrating CockroachDB with Airflow and dbt

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Modern data engineering workflows demand robust orchestration, reliable transformations, and databases that can scale with growing data volumes. Integrating CockroachDB with Apache Airflow and dbt (data build tool) creates a powerful stack for building production-grade data pipelines that combine the best of distributed databases, workflow orchestration, and analytics engineering. This integration enables data teams to … Read more

Building Real-Time Data Pipelines with CockroachDB and Kafka

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Modern applications demand real-time data processing capabilities that can scale globally while maintaining consistency and reliability. Building such systems requires careful consideration of database architecture and event streaming infrastructure. CockroachDB, a distributed SQL database, paired with Apache Kafka, the industry-standard event streaming platform, provides a powerful foundation for creating robust real-time data pipelines that can … Read more

Data Engineers vs Data Scientists Explained

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The data revolution has created two critical roles that often confuse people outside the field—and sometimes even those within it. Data engineers and data scientists both work with data, both require technical skills, and both are essential for modern data-driven organizations. Yet these roles are fundamentally different in their focus, responsibilities, and the value they … Read more

CDC Pipeline Architecture on AWS Using Firehose and Glue

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Change Data Capture (CDC) has become essential for modern data architectures, enabling real-time data synchronization, analytics, and event-driven workflows. When building CDC pipelines on AWS, combining Kinesis Firehose with AWS Glue creates a powerful, serverless architecture that scales automatically and requires minimal operational overhead. This approach leverages AWS-managed services to capture database changes, stream them … Read more

Debezium Architecture Explained for Data Engineers

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Change Data Capture (CDC) has become essential for modern data architectures. When you need to replicate database changes in real-time, synchronize data across systems, or build event-driven architectures, CDC provides the foundation. Debezium has emerged as the leading open-source CDC platform, but understanding its architecture is crucial for implementing it effectively. This isn’t just another … Read more

Online Learning Algorithms for Streaming Data: Adapting in Real-Time

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In an era where data flows continuously from countless sources—social media feeds, financial markets, IoT sensors, user interactions, and network traffic—the traditional batch learning paradigm struggles to keep pace. Batch learning assumes you can collect all your data, train a model once (or periodically retrain), and deploy it until the next training cycle. But what … Read more

How Companies Manage Big Data

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In today’s digital economy, companies generate and collect data at unprecedented scales. From customer transactions and sensor readings to social media interactions and log files, organizations face the challenge of managing massive volumes of diverse data that arrive at high velocity. Successfully managing big data has become a critical competitive advantage, enabling companies to make … Read more

Streaming CDC Data from MySQL to S3

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Change Data Capture (CDC) has become essential for modern data architectures that need to keep data warehouses, analytics platforms, and downstream systems synchronized with operational databases in near real-time. Streaming CDC data from MySQL to Amazon S3 creates a powerful foundation for analytics, machine learning, and data lake architectures while maintaining a complete historical record … Read more

Schema Evolution in Data Pipelines: Best Practices for Smooth Updates

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Data pipelines are living systems. Business requirements change, applications evolve, and data sources transform over time. Yet many data engineering teams treat schemas as static contracts, leading to broken pipelines, data loss, and frustrated stakeholders when inevitable changes occur. Schema evolution—the ability to modify data structures while maintaining pipeline integrity—is not just a nice-to-have feature. … Read more