Enterprises in the retail, advertising, healthcare, and financial sectors have a pressing need to deliver data and insights to their customers immediately. These range from seasonal priority to mission critical data delivery initiatives.
This real-time data delivery is crucial across various industries. In FSIs, it enables instant risk management, fraud detection, algorithmic trading, and personalized customer offerings. Healthcare benefits from real-time patient monitoring and improved emergency response. Retailers leverage real-time data for dynamic pricing and efficient inventory management. The advertising industry relies on real-time processing for instantaneous bidding decisions, dynamic ad personalization, continuous performance monitoring, and precise audience segmentation. These use cases demonstrate how real-time data delivery, facilitated by platforms like Databricks, is transforming industries by enabling instant decision-making, personalized experiences, and optimized operations, ultimately driving business success in a dynamic data landscape.
Databricks is the premier platform for streaming and real-time data delivery capabilities. With the same codebase supporting both Batch and Streaming workloads, a sink (essentially a “write” of the data) can be done from both a Streaming source or a Batch source.
Databricks has two services tailor-made to deliver data at a real-time/near real-time basis
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Structured Streaming
Structured Streaming is a key service that powers data streaming on Databricks, providing a unified API for batch and stream processinghttps://www.databricks.com/product/data-streaming with the same codebase. It enables continuous data processing, allowing organizations to respond to incoming data immediatelyhttps://www.integrate.io/blog/the-only-guide-you-need-to-set-up-databricks-etl/ from a cloud storage bucket. Key features include:
- Unified batch and streaming APIs in SQL and Python
- Automatic scaling and fault tolerance
- Seamless integration with Delta Lake for optimized storage
Delta Live Tables
Delta Live Tables (DLT) offers a declarative approach to data engineering, simplifying the creation and management of streaming data pipelines. Benefits include:
- Automated data quality checks and error handling
- Simplified ETL processes for both batch and streaming data
- Reduced time between raw data ingestion and cleaned data availability
- Support for Streaming Pipelines with SQL Queries
- Ability to “sink” into multiple sources at once
Implementing real-time solutions with Databricks
To achieve the goal of reaching customers in 8 seconds or less, consider the following implementation strategies:
Optimized Data Ingestion
Use Auto Loader for efficient, real-time data ingestion from cloud object storage. This feature automatically detects schemas and optimizes the ingestion process, reducing latency in data processing.
Streamlined Processing
Leverage Databricks’ enhanced autoscaling capabilities to optimize cluster utilization by automatically allocating compute resources for each unique workload ensuring efficient processing of real-time data streams.
Unified Governance
Implement Unity Catalog for integrated governance across all data and AI assets, ensuring secure and compliant real-time data processing.
Best practices for real-time data delivery
- Configure Auto-Scaling Clusters: Set up auto-scaling clusters with appropriate instance types to balance resource utilization and cost-effectiveness.
- Implement Robust Error Handling: Establish automated systems for monitoring and handling errors to maintain reliable real-time ETL workflows.
- Utilize Delta Lake: Leverage Delta Lake for optimized storage and processing of both streaming and batch data
- Apply Real-Time Data Quality Checks: Use Delta Live Tables to perform real-time data quality checks and ensure data integrity.
- Monitor Performance: Regularly monitor pipeline performance using Databricks’ built-in tools and UI for immediate visibility into stream processing efficiency
Final thoughts
Real-time data delivery is becoming less and less of a “nice to have” and more than ever, a necessity for businesses aiming to stay competitive in a data-driven landscape. As you’ve seen, Databricks offers two effective approaches, each designed to handle different real-time processing needs. Whether you prioritize flexibility with unified APIs through Structured Streaming or automation with real-time data pipelines using Delta Live Tables, Databricks provides the right streaming solution to meet your specific business requirements.
With deep industry expertise and a proven track record in offering real-time data solutions, zeb can help you navigate these choices, implement best practices, and optimize your data strategy for maximum impact.
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