Kafka vs Google Cloud Pub/Sub: 2025 Comparison

CapabilityConfluent Cloud (Kafka)Google Cloud Pub/Sub
RetentionConfigurable per topic (hours → infinite via log compaction).Default 7 days; up to 31 days for subscription retention after configuration. Export to Cloud Storage for long-term replay.
ReplayOffset-based; consumers can seek to any committed offset within retention.Seek/Replay using snapshots or timestamps within retention window; Cloud Storage + Dataflow for archival replay.
OrderingPartition ordering guaranteed; use multiple partitions for parallelism.Ordering keys guarantee per-key ordering; without keys ordering is best-effort.
Delivery SemanticsAt-least-once; exactly-once semantics available for transactions and idempotent producers.At-least-once by default; exactly-once achievable with Dataflow or idempotent subscribers.
LatencyLow-latency (sub-50 ms) when clients reside near the cluster; depends on partition placement.Typically 60–100 ms median within a region; no latency SLA but scales automatically.
Availability SLA99.95% per region. Multi-region clusters available (see pricing).99.95% per region; regional or multi-region topics available.
Schema SupportManaged Schema Registry (Avro/JSON/Protobuf).Pub/Sub topic schemas (Avro, Protobuf, JSON) with validation.
Security & IAMAPI keys, role-based access, service accounts; integrate with AWS/GCP/Azure networking (PrivateLink, VPC Peering).Native Google IAM, CMEK encryption, VPC Service Controls (push/pull except legacy push).
Stream ProcessingKafka Streams, ksqlDB, Connect ecosystem.Cloud Dataflow (Apache Beam), Data Fusion, or 3rd-party stream processors.
Pricing (illustrative)Charged by throughput (GB ingested/egressed), partitions, and storage.Pay per request plus data volume; sustained use discounts for commitment tiers.

Picking the Right Service

Choose Confluent Cloud when you need Kafka protocol compatibility, fine-grained control over partitions/retention, or plan to reuse Kafka Streams/Connect tooling across clouds.

Choose Google Cloud Pub/Sub when you prefer a fully managed service tightly integrated with GCP IAM, Cloud Logging, and Dataflow, or when infrastructure teams want global topic replication without managing brokers.

Migration Tips

  • Map producers/consumers to equivalent client SDKs; Kafka clients cannot talk to Pub/Sub without a connector layer.
  • For long-term replay on Pub/Sub, schedule Dataflow jobs to archive topics to Cloud Storage and reload via seek when needed.
  • Evaluate egress costs: cross-region consumers on Confluent or Pub/Sub can trigger additional charges.

References