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275 questions, 991 terms and 600 topics in 30 areas.
37 results for “CDC to Stream”
Transaction Log Stream
Change events derived from a database's write-ahead log — faithful to the table's mutations and to its internal model rather than to the business's.
Change Data Capture
Publishing a stream of a database's row-level changes by reading its replication log, without modifying the application that owns it.
Log-Based Ingestion
Building the pipeline around a database's own change log — an initial snapshot followed by a continuous delta stream, with the two stitched together.
CDC Initial Snapshot
The consistent full copy taken when a CDC pipeline starts, before streaming begins — and the step that determines whether the target is correct.
Changelog Stream
A stream whose records are keyed updates, so replaying it from the beginning reconstructs a table — the same information in the other of its two forms.
Event Stream
An append-only, retained log of events that many independent consumers read at their own position, and can re-read.
Event Stream Versioning
Transforming an old event version into the current shape when it is read, allowing a stored event history to be interpreted by evolved code.
Log-Based CDC
Capturing changes by reading the database's own write-ahead log, which sees every change with no load on the source and no application involvement.
Query-Based CDC
Detecting changes by repeatedly querying for rows modified since the last run — simple, universally available, and lossy in specific ways.
Stream Enrichment
Attaching reference data to a stream by lookup against a materialised table rather than by joining two unbounded streams.
Stream-Table Duality
The equivalence between a stream of changes and a table of current state — each can be derived from the other.
Value Stream
The end-to-end sequence of activities that delivers a result to a customer, viewed across whatever departments and systems it happens to cross.
Checkpoint Interval
How often a stateful processor persists its state and offsets, which trades steady-state overhead against how much work is redone after a failure.
Consumer Group
A set of consumers that cooperatively read one stream, with each partition assigned to exactly one member, so the group collectively processes every message once.
Keyed State Size
The total state a job holds per key across all keys, which governs memory, checkpoint duration and recovery time.
Materialized View
A precomputed, stored result of a query, refreshed on a schedule or from a change stream, read instead of recomputing.
Offset Management
How a consumer records its position in a stream, and the decision that determines whether processing is at-least-once or at-most-once.
Reactive Streams
A specification for asynchronous stream processing in which the consumer requests a specific number of items, making backpressure part of the protocol rather than an afterthought.
TCP/IP
The layered protocol suite underneath essentially all application traffic — IP routes packets, TCP turns them into a reliable ordered stream.
Windowing
Grouping an unbounded stream into finite chunks so aggregation can produce results, defined over event time rather than arrival time.
A team proposes exposing their service's database change stream via CDC so other teams can consume it, avoiding the work of building an event API. What is your assessment?
Name what is actually being proposed The proposal is to publish the service's internal schema as its integration contract. CDC does not emit domain events; it e
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 downstream team needs to react to order changes. The order service can publish events, or they can consume CDC from its database. Which, and why?
The recommendation: published events, with CDC as the mechanism if needed The distinction that matters is what the consumer becomes coupled to . CDC consumed di
Delivery feels slow and leadership wants a productivity initiative. You propose mapping the value stream first. What will you map and what do you expect to find?
Map every step from request to delivered change, with two numbers each Work time — how long the step actually takes when someone is doing it. Wait time — how lo
For each of these, choose a queue or a stream and justify it — order fulfilment tasks, an audit trail, cache invalidation, and rebuilding a search index.
Order fulfilment tasks — queue Each task is consumed once by one worker and is then irrelevant. Nothing re reads it; no second consumer needs the same task. Wha
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
CDC to Stream
Turning database changes into an event log, and how that differs from a domain event.
CDC Pipeline Design
Building on a change stream: snapshot plus delta, tombstones, and merge into the target.
Stateful Stream Processing
Keyed state, state backends, checkpoint size, and the restore time that follows.
Stream Processing Frameworks
Flink, Kafka Streams, Spark Structured Streaming — state, checkpointing and recovery.
Stream-Table Duality
A changelog and a table as two views of the same thing, and materialising between them.
Change Data Capture
Turning a database's replication log into a stream, and its coupling risk.
Legacy Integration Patterns
Anti-corruption layers, adapters and CDC against systems that cannot change.
Platform Team Topologies
Stream-aligned, enabling, complicated-subsystem and platform teams, and their interactions.
Team Topologies
Stream-aligned, platform, enabling and complicated-subsystem teams.