Harness Change Data Capture for Efficient Data Processing and Analysis

Boost Data Synchronization and Streamlined Processing with Kestra's CDC Capabilities

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Harness Change Data Capture for Efficient Data Processing and Analysis
What is Change Data Capture ?
Change Data Capture (CDC) tracks and captures data source alterations for efficient processing and analysis. Kestra's CDC features allow businesses to synchronize and manage data effectively, maintaining updated data warehouses and analytics platforms with minimized resource use.

Streamlined Data Analysis for Financial Institutions

Efficient Data Analysis through Change Data Capture

Financial institutions require up-to-date information from multiple sources like transactional databases, customer profiles, and market data feeds for informed decision-making. Synchronizing their data warehouse and analytics systems with these sources is crucial.

Diagram illustrating Kestra's Change Data Capture process, with PostgreSQL for databases, Apache Kafka for streaming data, and Apache Spark for analytics processing

CDC Implementation for Seamless Data Synchronization

Utilizing Kestra's Change Data Capture capabilities, financial institutions can detect and capture data source changes promptly.

For example: the institution uses PostgreSQL for transactional databases, Apache Kafka for streaming data, and Apache Spark for analytics processing. Kestra's CDC capabilities help detect changes in the PostgreSQL database and publish the changes to Kafka topics. Apache Spark then consumes the Kafka messages, processes the data, and updates the data warehouse and analytics platforms.

Workflow Configuration and Management with Kestra

Kestra enables institutions to configure and manage CDC workflows with tasks such as data transformation, filtering, and aggregation, resulting in a consistent and up-to-date data view for accurate insights and decision-making.

Picture of tasks possible with Kestra Change Data capture like data transformation, filtering, and aggregation
Illustration showing Kestra's event-driven triggers that initiate workflows automatically upon data changes, such as inserting a new customer record into the PostgreSQL database

Event-Driven Triggers for Automatic Workflow Initiation

Kestra's event-driven triggers initiate workflows automatically as data changes occur, eliminating manual intervention and reducing data inconsistency risks.

For example: when a new customer record is inserted into the PostgreSQL database, Kestra detects the insert operation and automatically triggers a corresponding workflow. This workflow processes the new data and updates the data warehouse and analytics systems accordingly.

Integration with Existing Infrastructure

With Kestra's extensive integration capabilities, the financial institution can seamlessly connect its existing infrastructure and third-party tools, allowing for effortless data synchronization across various systems.

Image depicting Kestra's extensive integration capabilities, with logos of AWS, Fivetran, and Airbyte

Kestra - Empowering Data-Driven Success

Kestra's Change Data Capture capabilities enhance data management by enabling efficient data synchronization and processing. With Kestra's event-driven triggers, visual pipeline editor, and extensive integrations, businesses can maintain up-to-date data across their systems, leading to timely insights and better decision-making. Experience the benefits of Kestra's CDC solution and transform your data management processes today.

Key Features

Leveraging Kestra's Features

Efficient Data Capture

CDC allows you to track and capture data changes promptly, ensuring that your data pipelines remain current and provide you with accurate, actionable insights.

Seamless Integration with Data Sources

Integrates with various data sources, databases, and platforms, allowing you to track changes across your entire data ecosystem.

Scalable and Efficient Processing

Kestra is designed to handle high data volumes and can scale to meet your growing data needs.

Reduced Data Latency

Reduce data latency, ensuring that your data pipelines and analytics are always based on the latest information.

Data Versioning

Allow you to track and manage historical versions of your data for auditing, analysis, and compliance purposes.

Delayed Data Capture

Configure time delays for capturing data changes for handling time-sensitive data or for mitigating the impact of temporary data inconsistencies.

Ready to take your data department to the next level ?