¶ Querying Data Across SAP Vora and SAP HANA: Bridging Big Data and In-Memory Analytics
In today’s enterprise landscape, data resides in diverse platforms—from traditional relational databases to Big Data ecosystems. SAP Vora and SAP HANA together provide a comprehensive solution that combines the power of in-memory computing with distributed data processing. Querying data seamlessly across SAP Vora and SAP HANA enables organizations to leverage both detailed transactional data and large-scale distributed datasets for advanced analytics.
This article explores how to efficiently query data across SAP Vora and SAP HANA, the architecture involved, and best practices for integrating these two powerful SAP technologies.
¶ Understanding SAP Vora and SAP HANA
- SAP HANA is an in-memory, columnar database optimized for real-time transactional and analytical processing.
- SAP Vora is an in-memory, distributed computing engine designed to run on Hadoop and Apache Spark, enabling interactive analytics on Big Data.
Together, they allow enterprises to combine structured, enterprise data (SAP HANA) with semi-structured and unstructured Big Data (SAP Vora) for a unified analytical experience.
¶ Why Query Across Vora and SAP HANA?
- Unified Analytics: Access transactional data in SAP HANA alongside Big Data in Hadoop clusters via Vora.
- Enhanced Business Insights: Combine detailed business data with external data sources like IoT, social media, or logs.
- Performance Optimization: Push compute-intensive operations closer to the data source, reducing data movement.
- Flexibility: Choose where to execute queries depending on data location and processing requirements.
¶ Architecture for Querying Across SAP Vora and SAP HANA
- SAP Vora Distributed Engines: Includes relational, graph, time-series engines deployed on Hadoop/Spark.
- SAP HANA Database: In-memory database hosting enterprise transactional and master data.
- SAP Vora Server and Client: Facilitates communication and query execution.
- SAP HANA Smart Data Access (SDA) or Smart Data Integration (SDI): Provides virtual access or replication capabilities to Hadoop/Vora data.
- User Query: Initiated from SAP HANA or a BI tool, the query involves data residing in both SAP HANA and SAP Vora.
- Query Federation: SAP HANA uses SDA/SDI adapters to push parts of the query to SAP Vora.
- Distributed Execution: Vora executes its portion on the Hadoop cluster.
- Result Aggregation: SAP HANA aggregates results from its local tables and Vora’s output.
- Response: Combined results are returned to the user or application.
¶ How to Query Data Across Vora and SAP HANA
SDA enables SAP HANA to access remote data sources as virtual tables without data replication.
- Create a remote source in SAP HANA pointing to the SAP Vora server.
- Define virtual tables in SAP HANA mapping to Vora tables.
Example SQL to create a remote source:
CREATE REMOTE SOURCE VORA_SOURCE ADAPTER "VORA" CONFIGURATION 'host=vora-host;port=9090';
Then create a virtual table:
CREATE VIRTUAL TABLE VORA_CUSTOMERS AT VORA_SOURCE."default"."customers";
Use SQL to join and query data from SAP HANA local tables and Vora virtual tables seamlessly.
SELECT h.customer_id, h.customer_name, v.purchase_count
FROM hana_schema.customers h
JOIN VORA_SOURCE.default.customers_purchase_count v
ON h.customer_id = v.customer_id
WHERE v.purchase_count > 5;
- Push down filters and projections to Vora to minimize data transfer.
- Use statistics and query plans to optimize federated queries.
- Schedule data replication using SDI for frequently accessed datasets if needed.
- Use Virtual Tables for Real-Time Access: SDA virtual tables avoid data duplication and provide the latest data.
- Replicate for High Performance: Use SDI for critical datasets to improve query performance.
- Optimize Query Pushdown: Ensure as much of the query logic runs in Vora to reduce network overhead.
- Secure Data Access: Leverage SAP HANA and Vora security features to protect sensitive information.
- Monitor and Tune: Use SAP HANA and Vora monitoring tools to analyze query performance and tune accordingly.
- Customer 360 Analytics: Combine SAP HANA CRM data with social media sentiment data stored in Hadoop/Vora.
- IoT Analytics: Analyze sensor data in Vora and join with maintenance schedules in SAP HANA.
- Fraud Detection: Correlate transactional data in SAP HANA with network logs processed in Vora.
Querying data across SAP Vora and SAP HANA bridges the gap between enterprise transactional data and vast Big Data stores, enabling enriched analytics and better business insights. By leveraging technologies like SAP HANA Smart Data Access and SAP Vora’s distributed processing power, organizations can build flexible, high-performance analytical solutions that scale with their data needs.
Understanding the integration architecture and following best practices ensures seamless querying and efficient data processing, empowering businesses to make informed decisions faster.