Fintech & Banking
High transaction volume, strong consistency, full auditability and near-zero tolerance for downtime. Focus: isolation levels, idempotent writes, multi-region HA and regulation-compliant retention.
Industries
Every industry has its own constraints in the data layer: some need auditability, some campaign peaks, some long-term retention. Below are the patterns we meet again and again.
High transaction volume, strong consistency, full auditability and near-zero tolerance for downtime. Focus: isolation levels, idempotent writes, multi-region HA and regulation-compliant retention.
Sudden load at campaign peaks, stock and order consistency, low latency on the checkout path. Focus: read scaling, caching strategy, hot-table partitioning and queue-based writes.
Multi-tenant architecture, fast release cadence and predictable cost. Focus: tenant isolation, schema-migration discipline, usage-based scaling and noisy-neighbour control.
Sensitive personal data, KVKK/access controls, long-term retention and archiving. Focus: field-level encryption, access auditing, data masking and lifecycle management.
OT/IT integration, IoT telemetry streams, real-time reporting and field-outage scenarios. Focus: time-series storage, incremental aggregation, hybrid deployment and durable queuing.
On-prem/hybrid setups, strict compliance, disaster plans and vendor independence. Focus: open-source-first architecture, detailed runbooks and regular DR drills.
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