Search the practice set
275 questions, 991 terms and 600 topics in 30 areas.
60 results for “Streaming vs Batch”
Freshness Requirement
How stale data may be before the decision it supports degrades — the only question that justifies streaming over batch.
Active-Active vs Active-Passive
Whether all regions serve traffic simultaneously, or one serves while another waits to take over — a choice about which failure mode you would rather have.
Build vs Buy
The choice between developing a capability in-house and acquiring it, decided on differentiation and total cost rather than on feature lists.
Containment vs Eradication
Stopping an attacker's ongoing access versus removing their foothold entirely — sequential phases with different urgency and different risks of doing them wrong.
Cost vs Reliability Trade-off
The non-linear relationship between availability and spend, which makes each additional nine roughly an order of magnitude more expensive.
Delivery vs Maintainability
Choosing where to take deliberate shortcuts, based on which kinds of debt are cheap to repay and which compound.
Durability vs Availability
Two different storage guarantees — whether data survives, and whether it can be reached right now — routinely conflated because both are quoted in nines.
ETL vs ELT
Whether data is transformed before loading into the target or after it, which decides where the compute happens and how much raw history you keep.
Event Notification vs Event-Carried State
Whether an event carries only the fact that something happened, or also the data a consumer needs to act on it.
Fail-Fast vs Fail-Safe
Whether a component should stop immediately on detecting a problem, or continue in a degraded but safe mode — a choice that depends entirely on which outcome is worse.
Horizontal vs Vertical Scaling
Adding more machines versus making one machine bigger — and the fact that vertical is underrated for stateful tiers.
Layer 4 vs Layer 7 Load Balancing
Balancing on connection metadata (IP and port) versus on the content of the request (path, host, headers).
Managed vs Self-Managed
Trading control, portability and unit cost against the operational burden of running the thing yourself.
Monolith vs Microservices
A trade of deployment independence against distributed-systems complexity, decided by team topology far more often than by technology.
OLTP vs OLAP
Two workload shapes with opposite requirements — many small indexed transactions versus few large scans and aggregations — which is why they belong in different stores.
Operational vs Analytical Store
The separation between the store serving the application's transactions and the one serving reporting and analysis, and the mechanism connecting them.
Provisioned vs Serverless Capacity
Paying for a fixed database size continuously, versus paying for capacity consumed with automatic scaling — a crossover decision driven by duty cycle.
Re-architect vs Rebuild
Restructuring an existing system incrementally versus writing a replacement from scratch — and the strong evidence that incremental wins.
SQL vs NoSQL
A choice driven by access patterns, consistency requirements and query flexibility — not by data volume, which is the reason usually given.
Security vs Usability
A trade-off that is usually resolved by varying the control with the value of the action, rather than by choosing a uniform level of friction.
A business sponsor asks for a real-time data platform because "the competition has one". Reporting is currently a nightly batch that lands at 06:00 and nobody has complained. How do you handle this?
Do not answer the technology question "Real time platform" is a solution, and it has arrived without a problem attached. Answering it directly leads either to a
A streaming aggregation reports lower totals than the batch job it replaced. Both read the same source. What is likely happening?
The likely cause: late events dropped past the watermark The batch job reads a completed day and sees everything, including records that arrived hours after the
Your streaming aggregate reports 2% lower daily revenue than the batch reconciliation. Both are "correct". Explain what is happening and how you resolve it.
The likely cause: silently dropped late data The streaming job windows by event time and closes each window when the watermark passes. Records arriving after th
A CDC pipeline feeding your warehouse falls three hours behind during a source system's batch job, and the source's transaction log retention is 24 hours. What is the risk and what do you change?
The immediate risk Lag consumes the retention window. At three hours behind against a 24 hour retention, you have 21 hours of margin. If the consumer stops enti
A core mainframe system with no API supports nightly batch file exchange only. The business needs near-real-time order status. Design the integration.
Establish the real constraint "No API" usually means no API the mainframe team will build on your timeline . Find out what exists: message queue interfaces, dat
A vendor claims their streaming platform provides exactly-once processing. How do you evaluate the claim?
Ask where the guarantee ends Nearly always at the platform's boundary. Within it, state and offsets commit together, so internal state reflects each input once.
One customer's batch job saturates a shared service and degrades everyone. Rate limiting them fixes it, until the next customer does the same. What is the structural answer?
Why per customer rate limits keep failing A static limit is set from what that customer was doing, not from what the service can serve. It is reactive — you dis
Streaming vs Batch
The freshness requirement that actually justifies streaming, and the cost of assuming one.
Kappa vs Lambda
One pipeline replayed versus two pipelines reconciled, and the maintenance each carries.
Batch Orchestration
DAGs, dependencies, retries, and the difference between a schedule and an orchestration.
Build vs Buy
Differentiation versus table stakes, priced over five years.
Build vs Buy
Differentiation, five-year TCO, and the exit cost of each option.
Centralised vs Distributed
Shared platform leverage against team autonomy.
Change Advisory vs Automated Gates
Replacing a weekly board with evidence a machine produces on every change.
Change Management vs CD
Reconciling CAB-era controls with continuous delivery without pretending either away.
Control Design vs Operation
A control that is well designed and never runs fails exactly like one that is absent.
Cost vs Reliability
Each nine costing an order of magnitude, and pricing the failure instead.
Delivery vs Maintainability
Fast in the cheap places, careful in the expensive ones.
Erasure vs Immutability
Deletion obligations against event logs, backups and ledgers designed never to forget.
Event Streaming
Retained ordered logs, consumer offsets, partitions and replay.
Functional vs Non-Functional
Behaviour versus quality of behaviour, and why only the second constrains structure.
Guardrails vs Gates
Preventing a class of mistake automatically versus stopping to ask a human.
Horizontal vs Vertical Scaling
Scale out for stateless, scale up first for stateful.
Layer 4 vs Layer 7
Connection-level versus request-level balancing, and what each unlocks.
Managed vs Self-Managed
Trading control and unit cost against operational attention.
Monolith vs Microservices
A team-topology decision far more often than a technology one.
Orchestration vs Choreography
A coordinator that knows the flow, or services that react to events.
Performance vs Cost
Buying latency, and knowing what the last millisecond is worth.
Rebuild vs Re-architect
Why greenfield replacement fails, and the narrow cases where it does not.
Reliability vs Complexity
Mechanisms that add availability and add failure modes.
SQL vs NoSQL
Decided by access patterns and query flexibility, not by data volume.
Security vs Usability
Varying control by the value of the action rather than uniformly.
Self-Service vs Governed
Letting analysts move fast without four teams reporting four different revenues.
Serverless vs Containers
Spiky and event-driven versus sustained throughput.
Single vs Multi-Region
Driven by RTO, RPO and residency rather than by ambition.
Streaming & Real-Time Data
General material on continuous processing of unbounded data.
Streaming Cost
Always-on compute, retention and cross-zone traffic as the three bills that surprise.
Streaming Data
Windowing, watermarks, late arrivals and exactly-once semantics.