Kinesis vs Event Hubs vs Pub/Sub for Game Telemetry

Every live-service game runs on a river of events it never shows the player: a shot fired, a loot box opened, a match abandoned, a suspicious input pattern that might be a cheat. Someone has to carry that river somewhere useful, fast enough that a live-ops dashboard isn’t lying by the time anyone looks at it. By October 2026, three managed services do most of that carrying for game studios that don’t want to run their own Kafka cluster: Amazon Kinesis Data Streams, Azure Event Hubs, and Google Cloud Pub/Sub. They look interchangeable in a slide deck. They are not interchangeable in a bill or an incident report.

This comparison pulls the published numbers from all three vendors’ own documentation and lines them up for one specific job: moving player-event telemetry out of a game server and into something a live-ops team can query. Retention windows alone swing by more than 10x between the shortest and longest options, and that gap decides whether you can replay last week’s exploit or only yesterday’s.

Why Game Telemetry Needs a Different Lens Than General Messaging

Generic cloud messaging comparisons usually frame AWS Kinesis, Azure Event Hubs, and Google Cloud Pub/Sub around enterprise integration patterns: order confirmations, IoT sensor pings, log shipping. Game telemetry is a different animal. A single live match can emit hundreds of discrete events per second per player, bursts arrive in waves tied to matchmaking and patch-day spikes rather than smooth diurnal curves, and some of that data, anti-cheat signals especially, needs to be replayable days or weeks later when a ban appeal lands on a trust-and-safety queue.

That changes which spec rows actually matter. Raw throughput ceilings matter less for most studios than how predictably a service scales mid-spike, how expensive it is to keep three weeks of raw events around for a fraud investigation, and whether the pricing model punishes you for a launch-day traffic spike you can’t forecast. Those are the questions this piece answers, using the numbers each vendor actually publishes rather than marketing language.

AWS Kinesis Data Streams at a Glance

Amazon Kinesis Data Streams is AWS’s shard-based streaming service, and shards remain the core unit everything else is billed and sized around. According to AWS’s own big data analytics documentation, each shard supports 1 MB per second or 1,000 records per second on the write side, and 2 MB per second or 2,000 records per second on the read side, which is why a Kinesis sizing exercise for a game backend starts with counting expected events per second and dividing by those per-shard ceilings. Need more throughput during a launch? You add shards, either manually in provisioned mode or automatically in on-demand mode.

Retention is where Kinesis pulls ahead of both rivals on paper. The default window is 24 hours, extendable to 7 days, and AWS also offers long-term retention stretching all the way to 365 days, billed as a GB-month charge rather than a shard-hour charge once you’re past the first week. For a studio that wants to re-run a season’s worth of matchmaking telemetry through a new fraud model, that year-long ceiling is the single biggest differentiator in this comparison.

On-demand mode, which removed the need to manually provision shards, carries its own quirk worth knowing before you budget: AWS bills a regional account-level minimum of 25 MB/s ingested and 25 MB/s retrieved even if your actual traffic is lower, a detail documented in AWS’s Kinesis service overview. Small indie teams running a modest player base can end up paying for headroom they’ll only use once, at launch.

Azure Event Hubs at a Glance

Azure Event Hubs organizes capacity around throughput units in its Standard tier and processing units in Premium, and the ingress/egress split looks almost identical to Kinesis at the entry level: a Standard throughput unit handles 1 MB/s or 1,000 events/s in, and 2 MB/s or 4,096 events/s out, slightly more generous on the read side than a Kinesis shard. Microsoft’s own documentation on what Event Hubs actually is frames it as a real-time data streaming platform built for the ingestion tier, not as a general message queue, which is a useful distinction when you’re deciding whether it belongs next to or instead of a queue like Azure Service Bus in your architecture.

Retention tells a more layered story than Kinesis’s single long-term tier. Basic caps out at 1 day, Standard goes to 7 days, and both Premium and Dedicated extend to 90 days, according to Microsoft’s quotas documentation. That 90-day Premium ceiling beats Kinesis’s default 7-day extended window but falls well short of the 365-day long-term tier AWS offers. Premium also decouples throughput from a fixed per-unit number: Microsoft’s own Event Hubs Premium overview describes achievable throughput as workload-dependent rather than throttled to a hard per-PU ceiling, with namespaces supporting 1, 2, 4, 6, 8, 10, 12, or 16 processing units.

One practical wrinkle for anyone budgeting this out in October 2026: Microsoft’s public Event Hubs pricing page does not display literal per-unit dollar figures for Basic, Standard, or Premium tiers in the way AWS and Google do. The page shows placeholder pricing and routes shoppers toward a custom quote or the Azure pricing calculator, which makes a clean three-way dollar comparison harder to pin down than the spec sheets suggest.

Google Cloud Pub/Sub at a Glance

Google Cloud Pub/Sub skips the shard/throughput-unit abstraction entirely and bills by throughput volume instead, which is simpler to reason about but harder to forecast for bursty game traffic. Google’s pricing page lists a flat $40 per TiB for both publish and subscribe/delivery throughput, with a free allowance of 10 GiB of throughput per calendar month per billing account on the Message Delivery Basic SKU.

Pub/Sub’s quotas page sets the publish request size ceiling at 10 MB, meaningfully larger than the 1 MB event cap on Event Hubs, which matters if your anti-cheat pipeline ever needs to ship a full replay buffer rather than a compact event. Default message retention sits at 7 days, with a maximum of 31 days, the shortest long-tail retention window of the three services compared here. Regional throughput quotas scale from 200-400 MB/s in small regions up to 4 GB/s in large regions for both publishers and pull subscribers, a ceiling high enough that most studios will hit cost limits before they hit throughput limits.

Google also sells a leaner variant, Pub/Sub Lite, priced at $0.00625 per MiB-hour of throughput and $0.000054795 per GiB-hour of storage, per zone. It trades some of standard Pub/Sub’s operational simplicity for a lower floor price, which can matter for a studio running dozens of lower-traffic regional game servers that don’t each need full Pub/Sub throughput guarantees.

Specs Side by Side: The Full Comparison Table

Pulling every figure above into one table makes the trade-offs easier to scan. All numbers below come directly from each vendor’s published documentation as of October 2026.

Two rows do most of the explanatory work here. Retention spans from a 1-day default on Event Hubs to a 365-day ceiling on Kinesis, better than a 300x difference between the most conservative out-of-the-box setting and the most generous long-term option. And message size caps run from 1 MB on Event Hubs to 10 MB on Pub/Sub, a 10x gap that decides whether you can ship a compact JSON event or need to chunk a richer payload before it fits.

Pricing Breakdown: Shard-Hours, Throughput Units, and Per-TiB Billing

The three services don’t just charge different amounts, they charge for different things, which makes an apples-to-apples dollar comparison harder than the specs table above. AWS Kinesis in provisioned mode charges $0.015 per shard-hour in US East (N. Virginia), plus a separate per-million PUT payload unit charge for data ingested. Switch to on-demand mode and AWS instead charges $0.08 per GB ingested, with no fixed hourly shard charge, though the 25 MB/s minimum mentioned earlier still applies at the account level.

Google Cloud Pub/Sub is the most transparent of the three on paper: a flat $40 per TiB covers both publish and subscribe throughput once you’re past the 10 GiB monthly free allowance, with no separate shard or unit charge to track. That simplicity is also Pub/Sub’s main cost risk for a game studio. Because there’s no cheaper provisioned tier to fall back to, a traffic spike translates directly into a proportional bill increase, whereas Kinesis’s provisioned shard-hour model lets you lock in a known monthly floor regardless of whether you use the full capacity.

Azure Event Hubs is the outlier for a different reason: as of October 2026, its public pricing page does not surface literal per-unit dollar figures for the Basic, Standard, or Premium tiers the way AWS and Google do. The page displays tier structure and feature differences clearly, but the pay-as-you-go dollar amounts require either the Azure pricing calculator or a direct quote, which makes Event Hubs the hardest of the three to budget from public documentation alone.

To put the per-unit numbers into a concrete scenario: a mid-size live-service title pushing a hypothetical 500 GB of player-event data per day would land close to $1,200 per month on AWS Kinesis’s on-demand ingestion rate alone ($0.08/GB x 500 GB x 30 days), before retrieval and retention charges. The same volume on Google Pub/Sub, converting 500 GB/day to roughly 13.6 TiB/month, would run close to $546 per month on throughput alone after the free allowance, though that estimate ignores Pub/Sub’s separate delivery-side charges if a pipeline fans out to multiple subscribers. These are illustrative calculations built from each vendor’s published list price, not verified customer invoices, and actual bills will move with region, retrieval patterns, and subscriber fan-out.

Scaling that same math across a few different traffic tiers shows how the gap widens as a game grows, since Kinesis on-demand and Pub/Sub both bill linearly with volume while Event Hubs’ calculator-only pricing can’t be modeled the same way from public documentation alone.

These figures model ingestion/throughput charges only, using each vendor’s published per-GB or per-TiB list price, and deliberately exclude retrieval, retention, storage, and subscriber fan-out charges that would add to every cell in practice. Azure Event Hubs is left out of this specific table because its public pricing page does not expose a literal per-unit dollar figure to model against, which is itself part of the broader pricing-transparency finding in this comparison.

Throughput and Latency for Player-Event Workloads

None of the three vendors publish a directly comparable end-to-end p50/p99 latency benchmark in their public documentation, which is worth flagging plainly rather than papering over with an invented number. What is published, and what matters more in practice for a game backend, is how each service’s capacity model behaves under the kind of burst a launch day or a major patch creates.

Kinesis’s shard-based model means a sudden 5x spike in events either needs shards pre-provisioned ahead of the spike or an on-demand stream that scales automatically, with AWS absorbing the scaling decision internally. Event Hubs’ auto-inflate feature does something similar for throughput units, automatically increasing the count as traffic rises, though Microsoft’s quotas documentation notes Premium’s throughput ceiling is workload-dependent rather than a hard per-PU number, making capacity planning somewhat less predictable than Kinesis’s explicit per-shard math. Pub/Sub sidesteps unit provisioning entirely, which removes a whole class of capacity-planning work but means a traffic spike shows up as a proportional cost spike rather than a capacity-limit error, assuming you stay under the regional throughput quota.

For anti-cheat telemetry specifically, where a surge in suspicious-input events often correlates with exactly the kind of coordinated attack that also spikes overall traffic, that burst-handling behavior matters more than steady-state throughput numbers. A pipeline that silently throttles during the exact window a cheat wave hits is a worse outcome than a bigger bill.

Retention Limits and Replay for Live-Ops Debugging

Retention is the spec that most directly maps to a real live-ops workflow: how far back can a data scientist or trust-and-safety analyst reach when something looks wrong after the fact. Kinesis’s 365-day long-term retention tier is the clear outlier here, letting a studio replay a full season of matchmaking or economy events through a new model without having archived the raw stream separately. That capability costs extra as a GB-month charge beyond the first week, so it’s not a default-on setting, but it exists as a direct Kinesis feature rather than requiring a separate archival pipeline.

Azure Event Hubs tops out at 90 days on Premium and Dedicated tiers, which covers most quarterly live-ops review cycles but falls short of a full year. Google Pub/Sub’s 31-day maximum is the shortest of the three, meaning a Pub/Sub-based pipeline that needs longer-term replay has to actively export events into BigQuery, Cloud Storage, or another sink before the 31-day window closes, turning retention into an architectural decision rather than a configuration toggle.

That difference should factor directly into which service a studio picks for anti-cheat and fraud-adjacent telemetry specifically, since ban appeals and chargeback disputes routinely surface weeks or months after the original event, well past Pub/Sub’s native retention window and often past Event Hubs’ as well.

Ordering Guarantees and Delivery Semantics for Anti-Cheat Signals

Event ordering matters more for some telemetry types than others. A sequence of inputs feeding an anti-cheat model needs to arrive in the order it happened; a batch of cosmetic-purchase events for a nightly revenue report generally doesn’t. All three services provide ordering guarantees scoped to a partition, shard, or ordering key rather than globally across an entire stream, which is the standard pattern for horizontally scaled streaming systems and not a differentiator between them on its own.

Where the services diverge more is in how a pipeline handles duplicate delivery, since at-least-once delivery semantics are the norm across managed streaming services and exactly-once processing is typically achieved at the consumer layer through idempotent writes rather than guaranteed natively by the broker. Practically, that means a game studio’s downstream consumer, whether it’s a Lambda function, an Azure Function, or a Dataflow job, needs to de-duplicate events using something like a unique event ID, regardless of which of the three services sits upstream. None of the three eliminates that engineering requirement; the choice of service mostly changes which SDK and retry model you’re writing that de-duplication logic against.

Autoscaling: On-Demand Mode vs Auto-Inflate vs Pub/Sub Elasticity

AWS Kinesis offers two distinct operating modes, and the choice between them is really a choice about who owns capacity planning. Provisioned mode means you set the shard count and AWS charges per shard-hour regardless of utilization, giving predictable costs but requiring you to forecast traffic, including launch-day spikes, ahead of time. On-demand mode removes that forecasting requirement by scaling shards automatically, at the cost of the 25 MB/s minimum billing floor mentioned earlier and a usage-based price that rises with actual traffic.

Azure Event Hubs’ auto-inflate feature works in a similar spirit for the Standard tier, automatically raising the throughput unit count as ingress climbs toward the current ceiling, up to a maximum you configure in advance. Premium tier changes the equation again by billing per processing unit rather than per throughput unit, with Microsoft describing achievable throughput as dependent on the actual workload rather than a fixed per-PU number, which in practice means Premium capacity planning leans more on load testing your specific event shapes than on a published throughput table.

Google Pub/Sub removes the unit-provisioning step from the equation entirely. There’s no shard count or throughput unit to size; the service scales to the regional quota ceiling automatically, and the bill simply follows actual throughput. That’s the simplest operational model of the three for a small team, but it also means there’s no provisioned floor to fall back on if you want cost predictability independent of traffic, the way a fixed shard count gives you with Kinesis.

Downstream Analytics Integration for Live-Ops Dashboards

A streaming service is only half the pipeline; the other half is wherever a live-ops dashboard or a data science notebook actually reads the processed events. AWS pairs Kinesis Data Streams with Kinesis Data Firehose for near-zero-code delivery into S3, Redshift, or OpenSearch, and with Kinesis Data Analytics for in-flight SQL transforms, both of which read directly from the same shards a game server is already writing to.

Azure Event Hubs integrates with Azure Stream Analytics for similar in-flight processing, and its Capture feature automatically archives raw events to Azure Blob Storage or Data Lake Storage on a timer, which functions as a built-in safety net for the kind of longer-term retention the native Event Hubs tiers don’t offer on their own. That pairing, native short retention plus automatic Capture archival, is effectively how most Event Hubs-based game pipelines work around the 90-day ceiling discussed earlier.

Google’s path runs through Dataflow for stream processing and a direct Pub/Sub-to-BigQuery subscription type that writes events straight into a BigQuery table without a separate ETL job, which is one of Pub/Sub’s more underrated advantages for a studio whose live-ops team already lives in BigQuery dashboards. All three paths work; the deciding factor is usually which analytics warehouse the rest of the studio’s data stack already runs on, since that gravity tends to pull the streaming service choice along with it.

SDK and Client Library Support Across Languages

Game backends rarely run on a single language, which makes SDK coverage a practical concern rather than a footnote. A studio shipping a C++ game server, a Go-based matchmaking service, and a Python data pipeline needs client libraries across all three without stitching together unofficial wrappers. All three streaming services ship first-party SDKs for the major server-side languages a game backend is likely to use, including Java, Python, Node.js, .NET, and Go, through each vendor’s broader cloud SDK (the AWS SDK, the Azure SDK, and the Google Cloud client libraries respectively), rather than a standalone SDK scoped just to the streaming product.

Where the three diverge is in how directly a game engine talks to them. None of Kinesis, Event Hubs, or Pub/Sub ships an official Unity or Unreal Engine plugin, which means every studio in this comparison is writing a thin server-side relay layer regardless of provider: the game client or game server reports events to a backend service over its own protocol, and that backend service is what actually calls the Kinesis, Event Hubs, or Pub/Sub SDK. That’s a deliberate security boundary as much as a technical one, since none of the three vendors wants a game client holding direct write credentials to a production event stream, where a reverse-engineered client could be used to inject bogus telemetry.

That shared pattern, relay server in the middle rather than a direct client connection, is also why the migration guide later in this piece treats a cloud switch as a backend rewrite rather than a client-side patch. The game build itself typically doesn’t need to change at all; only the relay service and its downstream consumers do.

5 Real-World Use Cases for Game Studio Telemetry Pipelines

These scenarios are illustrative architecture patterns built from the published capabilities above, not confirmed deployments at named studios, since no official case study from any of the three vendors was available to cite for a specific game’s production pipeline.

• Battle royale anti-cheat telemetry: A studio running a 100-player battle royale mode needs sub-second ingestion of input-pattern events during matches, long enough retention to investigate ban appeals weeks later, and a direct path into a fraud-detection model. Kinesis’s 365-day long-term retention and native Lambda integration fit that replay requirement better than Pub/Sub’s 31-day ceiling.
• Mobile free-to-play IAP and economy events: A mobile studio tracking in-app purchase events and virtual currency balances for a BigQuery-based live-ops dashboard benefits from Pub/Sub’s direct BigQuery subscription type, skipping a separate ETL hop between the event stream and the dashboard.
• Cross-platform MMO server health telemetry: A studio already standardized on Azure for its backend, perhaps using PlayFab for player data, can route server health and session events through Event Hubs into Stream Analytics for near-real-time ops alerting, keeping the whole pipeline inside one cloud’s IAM and networking boundary.
• Esports tournament match-event archival: A publisher running sanctioned esports events needs a complete, replayable record of every match event for dispute resolution and broadcast overlays, a case where Kinesis’s long-term retention tier directly matches the multi-month review window tournament disputes can take.
• Indie co-op game launch-day spike handling: A small team with an unpredictable launch-day player count benefits from Pub/Sub’s lack of a unit-provisioning step, since there’s no shard count to under-forecast and no auto-inflate ceiling to configure in advance, trading some cost predictability for operational simplicity during the riskiest week of a game’s life.

Migration Guide: Moving a Game Telemetry Pipeline Between Clouds

Studios rarely start from a blank slate; more often a team outgrows its original choice or a broader company cloud strategy forces a switch. Here’s the general shape of that move, regardless of which direction you’re migrating.

1. Inventory every producer and consumer currently reading from or writing to the existing stream, including game servers, Lambda/Function/Dataflow jobs, and any dashboard subscriptions, since each one needs its SDK and endpoint updated.
2. Map your current retention usage to the destination service’s tiers before migrating. If you rely on Kinesis’s 365-day long-term retention today, moving to Pub/Sub’s 31-day ceiling means standing up a BigQuery or Cloud Storage export first, not after the cutover.
3. Stand up the destination stream (new Kinesis stream, Event Hub, or Pub/Sub topic) and run it in parallel with the existing pipeline rather than cutting over in one step, so you can compare event counts and catch dropped messages before fully committing.
4. Update producer SDKs in game servers to dual-write to both the old and new streams during the parallel-run period. Most game server frameworks isolate telemetry emission behind a thin wrapper, which is the right layer to swap the underlying client library.
5. Rebuild downstream consumers against the new service’s delivery model. A Kinesis Lambda trigger, an Event Hubs-triggered Azure Function, and a Pub/Sub push subscription are functionally similar but not code-compatible, so this step is a rewrite, not a config change.
6. Validate ordering and de-duplication logic against the new service specifically, since consumer-side idempotent-write logic written for one vendor’s retry behavior doesn’t automatically carry over correctly to another’s delivery semantics.
7. Run both pipelines in parallel through at least one full traffic cycle, including a weekend peak and a patch-day spike if your release calendar allows it, before decommissioning the original stream and its retention data.
8. Archive any retention window you’re about to lose. If the source service held 90 days of Event Hubs Capture data you need for an open investigation, export it to cold storage before shutting down the old namespace.

Budget real calendar time for step 3’s parallel-run period specifically. Rushing the cutover is the most common way studios discover a dropped-event bug only after the old pipeline is already gone and there’s nothing left to compare against.

Common Mistakes Studios Make Picking a Telemetry Service

A handful of avoidable mistakes show up repeatedly when a studio picks one of these three services without mapping its own event volume and replay needs against the published limits first.

The first is sizing Kinesis provisioned shards for average traffic instead of peak traffic, then watching the stream throttle during exactly the matchmaking surge a Friday night patch creates. The per-shard ceilings of 1 MB/s or 1,000 records/s in, and 2 MB/s or 2,000 records/s out, are hard limits, not soft targets, and a studio that provisions for its average Tuesday afternoon load will get throttled the first time a content update drives a weekend spike. On-demand mode exists specifically to avoid this failure mode, at the cost of the 25 MB/s minimum billing floor discussed earlier.

The second is assuming Azure Event Hubs’ default 1-hour retention is a safe baseline for anything beyond pure real-time alerting. A studio that discovers a cheating wave three days after it happened, a common timeline once player reports start accumulating, will find the raw Event Hubs stream has already aged out unless Capture archival was switched on from day one. Capture isn’t retroactive; it only archives events written after it’s enabled, so turning it on after an incident doesn’t recover the data.

The third is treating Google Pub/Sub’s lack of shard provisioning as a reason to skip load testing entirely. Pub/Sub still enforces regional throughput quotas, from 200-400 MB/s in small regions up to 4 GB/s in large ones, and a studio that never tests against those ceilings can still hit a wall during an unexpectedly large launch, just with less warning than a Kinesis shard-count error would have given them.

The fourth, and most expensive, is forgetting that retention and storage are billed separately from ingestion on all three services. A studio that budgets only for the per-GB or per-TiB throughput rate and ignores the GB-month charge for Kinesis extended or long-term retention, or the storage cost baked into Event Hubs Capture’s destination storage account, routinely gets a bill that looks nothing like its back-of-envelope estimate.

Pros and Cons of Each Platform

AWS Kinesis Data Streams

• Pros: Up to 365 days of retention for long-term replay; explicit per-shard throughput math makes capacity planning predictable; tight native integration with Firehose, Lambda, and the rest of the AWS analytics stack.
• Cons: On-demand mode’s 25 MB/s minimum billing floor can overcharge low-traffic indie titles; provisioned mode requires manual shard forecasting ahead of spikes; tied most tightly to the AWS ecosystem of any of the three.

Azure Event Hubs

• Pros: Auto-inflate smooths out traffic spikes without manual intervention; Capture provides automatic long-term archival without a separate pipeline; Premium’s capacity-based model can absorb uneven workloads better than a fixed per-unit ceiling.
• Cons: Native retention tops out at 90 days, short of Kinesis’s year-long option; public pricing page doesn’t publish literal per-tier dollar figures, complicating budget planning; 1 MB max event size is the tightest of the three services compared.

Google Cloud Pub/Sub

• Pros: Simplest pricing model of the three, with no shard or unit provisioning to manage; direct BigQuery subscription type removes a full ETL hop for live-ops dashboards; 10 MB max message size is the most generous of the three.
• Cons: 31-day maximum retention is the shortest of the three, forcing an early export decision for anything needing longer replay; no provisioned tier means no fixed cost floor during unpredictable traffic; lower-cost Pub/Sub Lite trades away some of standard Pub/Sub’s operational simplicity.

Which Should You Choose? 5 Use-Case Recommendations

Rather than a single universal winner, the right pick tracks closely with which of these five situations best describes your studio.

• Your backend is already deep in AWS (GameLift, DynamoDB, Lambda): Pick AWS Kinesis Data Streams. The retention ceiling and native Firehose/Lambda integration pay off fastest when the rest of your stack is already there.
• Your live-ops team lives in BigQuery dashboards: Pick Google Cloud Pub/Sub. The direct Pub/Sub-to-BigQuery subscription type removes an entire integration layer other options require.
• You’re standardized on Azure and PlayFab for backend services: Pick Azure Event Hubs. Staying inside one cloud’s networking and IAM boundary outweighs the shorter native retention window for most teams in this position.
• You need months of replayable anti-cheat or fraud telemetry: Pick AWS Kinesis Data Streams for its 365-day long-term retention tier, or budget for aggressive Event Hubs Capture archival or early Pub/Sub exports if you’re locked into those platforms.
• You’re a small indie team that can’t forecast launch-day traffic: Pick Google Cloud Pub/Sub or Kinesis on-demand mode. Both remove manual capacity provisioning, trading some cost predictability for one less thing to get wrong during your riskiest week.

The Verdict: Our Pick for Game Telemetry Pipelines

There’s no single correct answer here, but the published data points toward a clear default: for a game studio whose telemetry needs include any meaningful anti-cheat, fraud, or live-ops replay requirement, AWS Kinesis Data Streams is the strongest general-purpose pick, mainly because its 365-day long-term retention tier is simply not matched by Event Hubs’ 90-day ceiling or Pub/Sub’s 31-day maximum. That retention gap, more than any throughput or pricing difference, is the spec that determines whether a studio can answer what actually happened months after the fact.

Google Cloud Pub/Sub is the better pick specifically for teams whose priority is operational simplicity and a direct line into BigQuery, and it remains the most transparent of the three on pricing, with a flat $40/TiB rate anyone can read off the public pricing page without a calculator. Azure Event Hubs earns its place for studios already committed to the Azure and PlayFab ecosystem, where staying inside one cloud boundary is worth more than an extra few hundred days of native retention, as long as the team builds Capture-based archival into the pipeline from day one rather than discovering the 90-day ceiling after the fact.

Frequently Asked Questions

Which service is cheapest for a small indie game’s telemetry pipeline?

Google Cloud Pub/Sub generally works out cheapest at low volume, since its 10 GiB free monthly throughput allowance and flat $40/TiB rate carry no fixed shard-hour or throughput-unit cost the way Kinesis and Event Hubs do, even in their cheapest tiers.

Can AWS Kinesis or Azure Event Hubs guarantee exactly-once event processing?

Neither service, nor Google Pub/Sub, natively guarantees exactly-once delivery at the broker level. All three operate on an at-least-once delivery model, and exactly-once processing has to be implemented at the consumer layer through idempotent writes keyed on a unique event ID.

How long can I replay player-event data with Google Pub/Sub?

Up to 31 days, which is Pub/Sub’s published maximum message retention period. Anything you need to replay beyond that window has to be exported to BigQuery, Cloud Storage, or another sink before the 31-day retention expires.

Can I switch cloud providers without rewriting my game’s telemetry pipeline?

Not without meaningful engineering work. Producer SDKs, consumer trigger models, and delivery semantics differ enough between Kinesis, Event Hubs, and Pub/Sub that a migration is a genuine rewrite of the ingestion and consumption layers, not a configuration change, as outlined in the migration guide above.

What happens if my game’s event volume spikes during a launch?

Kinesis on-demand mode and Event Hubs auto-inflate both scale capacity automatically, though Event Hubs auto-inflate only raises throughput units up to a ceiling you configure ahead of time. Pub/Sub has no provisioning step to scale at all, since it bills purely on throughput, but all three still cap out at their respective regional or account-level quotas during an extreme spike.

Is Azure Event Hubs Premium worth it for live-ops analytics?

It’s worth it mainly for the retention jump, from 7 days on Standard to 90 days on Premium, and for workload-dependent throughput that isn’t throttled to a fixed per-unit ceiling. Studios that don’t need either of those should evaluate whether Standard tier auto-inflate already covers their traffic pattern before paying for Premium.

Which service integrates best with BigQuery for live-ops dashboards?

Google Cloud Pub/Sub, by a clear margin, since it offers a direct Pub/Sub-to-BigQuery subscription type that writes events into a BigQuery table without a separate Dataflow or ETL job. Kinesis and Event Hubs can both reach BigQuery too, but through an extra integration hop that Pub/Sub skips natively.

Do I need Kafka instead of any of these managed services?

Only if you need full control over partition rebalancing, custom retention policies beyond what any of the three vendors publish, or a multi-cloud deployment that doesn’t want to depend on a single provider’s managed service. For most game studios, the operational overhead of running Kafka outweighs those benefits compared with a managed option from this comparison.