Zizo: Scalable Big Data Lakehouse & Telemetry Platform
Designed a modern Apache Iceberg lakehouse supporting high-concurrency analytical queries across tens of terabytes of multi-tenant enterprise data.
The Challenge
Zizo’s monolithic database architecture hit hardware compute limits under multi-tenant analytical query volume. Queries took minutes to execute, and licensing costs were doubling annually.
The Solution & Architecture
WDL modernized their infrastructure into a serverless lakehouse architecture using Apache Iceberg open table formats on Amazon S3 with Athena/Trino compute engines and automated compaction.
Project Metadata
Key Technical Capabilities Delivered
Architectural components engineered specifically to resolve the client's scaling hurdles.
Open Table Architecture
Eliminated vendor lock-in by implementing Apache Iceberg, granting ACID transactions and time-travel querying on commodity S3 storage.
Partition Pruning & Compaction
Automated background compaction jobs to optimize small files, cutting Trino query execution scan times by over 80%.
Granular Multi-Tenant Access
Row-level and column-level security policies enforcing strict tenant data isolation at the storage level.
Technologies Used
Build Fast, Scale Reliably
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Validate Data Strategy
Technical audit and architecture blueprint to validate pipeline viability.
Build Data MVP / Foundation
Production-ready automated pipeline and live analytics lakehouse delivered in just 20 days.