Espresso is LinkedIn's strategic distributed, fault-tolerant NoSQL database that powers many LinkedIn services. Espresso has a large production footprint at LinkedIn, with close to a hundred clusters in use, storing about 420 terabytes of source-of-truth (SoT) data and handling more than two million queries per second at peak load.
This talk discusses our strategy for migrating one of our internal services (Babylonia) from using Oracle to using Espresso. We will present an overview of the Espresso platform and its quality attributes that motivated the migration, as well as the particulars of how we accomplished the migration. Our core requirement was to keep Babylonia running uninterrupted throughout the migration process. These same concerns are common to many database migrations, not only at LinkedIn. The talk covers the steps we took to keep the service running through the transition without affecting our clients.
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