Sygnia successfully migrated their security data lake from Elasticsearch to Snowflake, resulting in improved operations, reduced costs, and empowered analysts. They faced challenges with cost, retention, and indexing in Elasticsearch. Snowflake's separation of compute and storage, cost efficiency, scalability, and SQL capabilities were driving factors in the decision to switch. The migration process involved testing in a development environment, involving analysts early, monitoring, scaling up, and migrating production environments. The impact of the migration included cost reduction, limitless data storage, enhanced scalability, operational efficiency, and a better user experience. Lessons learned included the benefits of ingestion with Snowpipes, good auto-clustering, activating top-k queries by default, enabling search optimization, and optimizing the use of UDFs.
Table of contents
Building a Security Data Lake for the Future: Sygnia’s Migration from Elasticsearch to SnowflakeWhat We DoHow We Do ItBackgroundWhy Snowflake?First Steps in the Migration ProcessOptimizationsThe Migration ProcessThe ImpactLessons LearnedFinal ThoughtsSort: