Run Analytical Workloads on Transactional Database at Scale with TiDB
Database innovations like Hybrid Transactional/Analytical Processing (HTAP) are transforming how we manage data, enabling analytical workloads to run directly on transactional databases at scale. This breakthrough reduces the need for separate systems, hardware, and complex processes like ETL, which often lead to data consistency issues and management overhead. Traditional data warehouses are no longer necessary for generating insights, as HTAP keeps everything within a single, unified system.
At this event, we will explore TiDB, a cutting-edge HTAP database that unifies Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) within a single architecture. TiDB removes the traditional barriers between transactional and analytical systems, allowing you to process and analyze data in real-time without the need for complex Extract, Transform, Load (ETL) workflows. By integrating both OLTP and OLAP within one platform, TiDB simplifies data management, enhances scalability, and ensures the consistency and quality of your data—all from a single source.
Join us as we dive into how TiDB transforms the database landscape, offering a seamless and efficient solution for organizations looking to unify their data strategy and harness the power of real-time analytics.
What You’ll Learn:
Unified Data Management: Experience the elegance of TiDB’s architecture, where all data is handled in a single system, allowing you to run both transactional and analytical queries from the same source. The App Server seamlessly sends all requests to the TiDB Server, which intelligently dispatches them to appropriate storage engines—resulting in a simple, scalable, and efficient solution.
Real-Time Data Exploration: Explore how TiDB enables businesses to access and query their data in real-time, leading to faster, data-driven decisions that enhance resource usage, improve customer experiences, and optimize business outcomes.
Scalability on Demand: TiDB’s architecture supports on-demand scalability, allowing companies to adapt their computing resources to meet business needs efficiently, whether predictable high loads like in gaming or unpredictable spikes like in financial services. This flexibility helps businesses reduce costs while ensuring performance is maintained during peak times.
Eliminate ETL Processes: Discover how TiDB removes the need for traditional ETL processes, minimizing the potential for errors, downtime, and user mistakes while ensuring that your data is always current, accurate, and ready for immediate use. With ETL eliminated, your teams can focus on higher-value tasks instead of managing cumbersome data transfers.
Why Attend:
Improve Business Agility: Learn how real-time analytics and transactions in TiDB can help you adapt quickly to market changes and customer needs.
Optimize Resource Usage: Understand how TiDB’s ability to scale on demand ensures that you’re only using (and paying for) the computing resources you actually need.
Enhance Operational Efficiency: Reduce workload and errors by eliminating ETL processes, freeing up staff to focus on innovation and customer satisfaction.
Who Should Attend:
Database Administrators and Software Engineers looking to implement HTAP solutions.
Data Scientists and Analysts seeking real-time data exploration.
Business Leaders and CTOs interested in reducing infrastructure costs while improving data accessibility and decision-making capabilities.
Speaker(s)
Daniel James (Senior Solutions Engineer at PingCAP)
Title: Practical applications of HTAP with TiDB
Agenda
What is HTAP (Hybrid Transactional/Analytical Processing)?
HTAP use cases
TiDB Overview
TiDB success stories
Matteo Merli (CTO at StreamNative):
Title: Ursa: Kafka-compatible data streaming on Lakehouse
Ursa is a Kafka-compatible data streaming engine built on top of a lakehouse, enabling users to store their topics and associated schemas directly in lakehouse tables. Ursa utilizes the innovations that StreamNative has developed to evolve Pulsar's storage layer from a disk-based shared storage layer to an object storage-based tiered storage system and to integrate with the lakehouse ecosystem. The Ursa engine simplifies the integration between data streams and lakehouse tables, drastically reducing the complexity of using bespoke integrations. In this talk, we will dive deeper into the details of the Ursa engine and how it leverages the lakehouse as a storage backend
Join us to see how TiDB can transform your data strategy—boosting efficiency, scalability, and adaptability—while keeping both your customers and employees satisfied.