Migrating from Elasticsearch/OpenSearch to Milvus
About the Webinar
Milvus 3.0 expands the range of search workloads teams can run in Milvus, with stronger full-text retrieval plus in-engine sorting, aggregation, and faceting. In our previous webinar, Simon Hearne, Solutions Architect at Zilliz, explored these search improvements and compared Elasticsearch and Milvus with live side-by-side queries.
In this follow-up session on September 2, Simon moves from comparison to migration. He’ll show how Zilliz Migration Service helps move data from Elasticsearch/OpenSearch into Milvus or Zilliz Cloud, then walk through a real migration workflow. He’ll also compare Elastic Cloud (ESS) and Zilliz Cloud, discuss deployment options across open-source Milvus, Zilliz Cloud, and Zilliz BYOC (Bring Your Own Cloud), and share lessons from customer migrations.
If you use Elasticsearch or OpenSearch today and are considering a migration, join us for the walkthrough and bring your questions for a ~20-minute live AMA.
What You’ll Learn
- The Migration Path — Understand the major stages and decisions in an Elasticsearch/OpenSearch migration to Milvus or Zilliz Cloud.
- Migration Tooling + Real Walkthrough — See how VTS (open-source migration tool) and Zilliz Migration Service (managed service built on VTS) help move Elasticsearch/OpenSearch data, then follow a real migration workflow.
- Licensing and Commercial Tradeoffs — Compare licensing models and the commercial considerations behind Elastic Cloud (ESS) and Zilliz Cloud.
- Deployment Choices — Compare open-source Milvus, Zilliz Cloud, and Zilliz BYOC across operating model, control, and security needs.
- Customer Migration Stories — See why real teams moved, how they approached the migration, and what they learned along the way.
- Live AMA — Bring your migration, architecture, and evaluation questions to a ~20-minute live discussion with Simon.
Join the Webinar
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Meet the Speaker
Join the session for live Q&A with the speaker
Simon Hearne
Solutions Architect
Simon Hearne is a Solutions Architect at Zilliz. He works closely with EMEA-based enterprise customers across verticals including IdV / facial recognition, legal case review, and social matching, enabling the design and implementation of GenAI, semantic search, and retrieval use cases using the Zilliz Cloud Vector Database. He brings experience from Elasticsearch and Akamai, and holds an MEng in Artificial Intelligence and an MSc in Data Science. Simon combines deep technical expertise in vector search with a strong focus on developer enablement, helping teams move from proof of concept to production with Milvus on Zilliz Cloud.