Data & AI Paris Meetup

​Join us and the organizers of Devworld Conference for an evening focused on Data & AI, bringing together professionals from Aerospike, ClickHouse, Databricks and Datadog working with modern AI tooling.

​We’ll explore real-world use cases, share practical workflows, and discuss how teams are integrating AI into their data and product stacks.

​Expect short talks, demos, and plenty of time for networking with others shaping the future of AI development.

Location: Datadog Office - 21 Rue de Châteaudun, 75009 Paris, France

Talks & Sessions:

👉 What Does It Take to Build a Real-Time Data Platform?
Speaker: Melvyn Peignon, ClickHouse

Modern AI systems—from recommendation engines to autonomous LLM agents—depend on fast, reliable access to fresh data. Feature retrieval, contextual enrichment, analytics, and observability all require sub-second responses, even at terabyte or petabyte scale, to deliver truly interactive experiences.

In this session, we’ll explore how ClickHouse enables real-time analytics at scale and how it fits into end-to-end AI architectures. We’ll dive into storage formats, indexing strategies, compression techniques, and query execution optimizations that deliver predictable low latency. We’ll also look at how ClickHouse integrates with the broader data ecosystem—data lakes, queues, and databases—to power modern analytical and AI workloads.

👉 AI Era: What It Means for Databases
Speaker: Nicolas Wlodarczyk, Engineer, Aerospike

The rise of AI is reshaping every layer of modern architecture—and databases are at the center of this transformation.

In this talk, Nicolas Wlodarczyk explores how the AI era is redefining how data is stored, accessed, processed, and delivered at scale.
Whether you’re building real-time applications, optimizing large-scale data pipelines, or preparing your infrastructure for AI-driven workloads, this session will give you a clear view of what’s changing—and what it means for you.
You’ll learn:

• Why traditional database assumptions no longer hold in AI-centric systems
• How real-time inference and massive parallelism reshape data access patterns
• The architectural shifts needed to support low-latency, high-throughput AI applications
• What modern databases must deliver to keep up with accelerating model complexity
• Practical steps to prepare your data infrastructure for the next wave of AI adoption

👉 Deep dive into Lakebase
Speaker: Yanic, Senior Solutions Engineer at Databricks

👉Session by Datadog to be decided!

Expect short talks, demos, and plenty of time for networking with others shaping the future of AI development.