BUILDING DATA ARCHIVE & RECOVERY FOR TRADING SYSTEMS High-frequency trading generates millions of transactions — driving up storage costs, slowing queries, and making recovery complex. Our archive-first approach keeps performance steady while ensuring historical data remains accessible when needed. What we built - Archive system handling 4.5M transactions (~9GB) per trading cycle. - Recovery workflow for historical data reprocessing and validation. - Metadata system for quick archive lookups without loading full datasets. - Dedicated compute environment to process and restore archived data without disrupting production. Core Components - Production flow: Real-time transactions → data lake → PostgreSQL. - Archive process: 3-month cycle → encrypted archives → cloud storage. - Recovery system: admin request → archive retrieval → analysis instance. Key benefits - Cost-efficient storage for long-term data retention. - No performance hit: archive old data, keep live queries fast. - Regulatory & audit-ready: easily retrieve historical records. - Cleaner data: reprocessed for accuracy, reducing system inconsistencies. Full technical implementation: https://lnkd.in/g6987gjV #Blockchain #finance #database #dwarves __ Dwarves Notes (https://memo.d.foundation/) combine our team’s collective know-hows, R&Ds, and operation approaches. Connect and learn alongside other tech fellows: - Discord: discord.gg/dwarvesv - Github: https://lnkd.in/gZZ2eZMu - Website: https://d.foundation
