Session: Options for real-time data pipelines

Siddharth Jain, Senior Engineering Manager @ Wayfair

Traditionally data pipelines have been set up for running as a batch. Now, cloud services give you the capability to run pipelines on a real-time basis. Real-time pipelines can drive operational efficiencies and provide an opportunity for businesses to react quickly. However, not all analytic needs deem a real-time approach, and knowing which do and do not is essential to achieving efficiency. Teams can easily fall into the trap of using services that enable real-time analytics, but it comes at a cost. Siddarth will discuss options like batching/micro-batching that can address most use cases at a cheaper cost.

Where & when?

Open Source Data Summit 2025 will be held on October 8th, 2025.

What is the cost of access to the live virtual sessions?

OSDS is always free and open for all to attend.

What is Open Source Data Summit?

OSDS is a peer-to-peer gathering of data industry professionals, experts, and enthusiasts to explore the dynamic landscape of open source data tools and storage.

The central theme of OSDS revolves around the advantages of open source data products and their pivotal role in modern data ecosystems.

OSDS is the annual peer hub for knowledge exchange that fosters a deeper understanding of open source options and their role in shaping the data-driven future.

Who attends OSDS?

OSDS is attended by data engineers, data architects, developers, DevOps practitioners and managers, and data leadership.

Anyone who is looking for enriched perspectives on open source data tools and practical insights to navigate the evolving data landscape should attend this event.

On October 2nd, 2024 we convened for discussions about:
  • Benefits of open source data tools
  • Cost/performance trade-offs
  • Building data storage solutions
  • Challenges surrounding open source data tool integration
  • Solutions for the cost of storing, accessing, and managing data
  • Data streams and ingestion
  • Hub-and-spoke data integration models
  • Choosing the right engine for your workload
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