Round 108

Data Consistency Model

Our distributed e-commerce platform is moving to a multi-region deployment to reduce latency for international users. A critical architectural decision is required regarding the consistency model for the global product inventory system. The goal is to maximize user experience while preventing 'ghost sales' (selling items that are out of stock). We face significant network partition risks and must balance the speed of 'Add to Cart' actions against the architectural complexity of distributed locks or reconciliation logic.

Dashboard

Status

DECIDED

Winner

C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions.

Majority

C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions.

Duration

6881 ms

Topic

Options

C Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions.
2.40 of 3 PPV winner
B Reservation-Based Sequential Consistency: Use a lightweight distributed lock or 'intent-to-buy' reservation that expires after 10 minutes. This moves the consistency check to the 'Add to Cart' stage rather than the final checkout, providing a smoother final payment experience at the cost of higher upfront coordination complexity.
0.60 of 3
A Inventory Partitioning (Siloed Allocation): Divvy the total stock into fixed pools assigned to specific geographic regions. A user in Europe only sees inventory allocated to Europe. If a region runs out, it must request a manual 'rebalance' from another region's pool, adding operational overhead but ensuring local consistency.
0.00 of 3
D Optimistic Quorum with Versioning: Allow writes if a majority of regions are reachable, providing a middle ground for latency. Use vector clocks to detect conflicts and a 'Last-Writer-Wins' or 'Smallest-Timestamp-Wins' resolution, accepting rare discrepancies in final stock counts.
0.00 of 3
E Eventual Consistency with Compensating Actions (AP): Prioritize availability and low latency by allowing local writes. Inventory counts may temporarily drift between regions. Over-selling is handled asynchronously via automated 'Order Canceled - Out of Stock' notifications and customer credit vouchers.
0.00 of 3

Checks

Baselines

PPV no gold answer
Majority no gold answer
Comparison PPV matched majority
k samples8
Agents3
Parsed samples 24 / 24
Quality split agent disagreement

PPV

Top Influences

GPT 5.4 mini · delegate 1.614
Gemini 3 Flash Preview · delegate 1.264
Claude Sonnet 5 · delegate 1.207

Samples

Answer Distribution

Claude Sonnet 5 B: 4 E: 3 C: 1
GPT 5.4 mini C: 8
Gemini 3 Flash Preview C: 6 A: 1 B: 1

PPV

Influences

Label Role Score
GPT 5.4 mini delegate 1.614
Gemini 3 Flash Preview delegate 1.264
Claude Sonnet 5 delegate 1.207

Voting matrix

Constructed Delegation Matrix

To / From Claude Sonnet 5 GPT 5.4 mini Gemini 3 Flash Preview
Claude Sonnet 5 0.0000.0000.207
GPT 5.4 mini 0.2640.0000.207
Gemini 3 Flash Preview 0.2640.0000.000
A 0.0000.0000.000
B 0.4710.0000.000
C 0.0001.0000.586
D 0.0000.0000.000
E 0.0000.0000.000

Embeddings

Sample Embeddings

24 samples
Claude Sonnet 5 sample #0 · B · 1536 dims B Claude Sonnet 5 sample #1 · E · 1536 dims E Claude Sonnet 5 sample #2 · B · 1536 dims B Claude Sonnet 5 sample #3 · B · 1536 dims B Claude Sonnet 5 sample #4 · E · 1536 dims E Claude Sonnet 5 sample #5 · E · 1536 dims E Claude Sonnet 5 sample #6 · C · 1536 dims C Claude Sonnet 5 sample #7 · B · 1536 dims B GPT 5.4 mini sample #0 · C · 1536 dims C GPT 5.4 mini sample #1 · C · 1536 dims C GPT 5.4 mini sample #2 · C · 1536 dims C GPT 5.4 mini sample #3 · C · 1536 dims C GPT 5.4 mini sample #4 · C · 1536 dims C GPT 5.4 mini sample #5 · C · 1536 dims C GPT 5.4 mini sample #6 · C · 1536 dims C GPT 5.4 mini sample #7 · C · 1536 dims C Gemini 3 Flash Preview sample #0 · C · 1536 dims C Gemini 3 Flash Preview sample #1 · B · 1536 dims B Gemini 3 Flash Preview sample #2 · C · 1536 dims C Gemini 3 Flash Preview sample #3 · C · 1536 dims C Gemini 3 Flash Preview sample #4 · C · 1536 dims C Gemini 3 Flash Preview sample #5 · A · 1536 dims A Gemini 3 Flash Preview sample #6 · C · 1536 dims C Gemini 3 Flash Preview sample #7 · C · 1536 dims C
Claude Sonnet 5 GPT 5.4 mini Gemini 3 Flash Preview

Samples

Agent Responses

Claude Sonnet 5 openai_compatible · anthropic/claude-sonnet-5
#0 B · Reservation-Based Sequential Consistency: Use a lightweight distributed lock or 'intent-to-buy' reservation that expires after 10 minutes. This moves the consistency check to the 'Add to Cart' stage rather than the final checkout, providing a smoother final payment experience at the cost of higher upfront coordination complexity. 1536 dims

Given the priorities—maximizing 'Add to Cart' speed while explicitly seeking to prevent ghost sales rather than merely compensating for them post-hoc—the reservation model best balances these needs. It shifts the consistency burden earlier in the funnel (at ca...

#1 E · Eventual Consistency with Compensating Actions (AP): Prioritize availability and low latency by allowing local writes. Inventory counts may temporarily drift between regions. Over-selling is handled asynchronously via automated 'Order Canceled - Out of Stock' notifications and customer credit vouchers. 1536 dims

Eventual consistency with compensation offers the best balance for e-commerce scale, prioritizing low-latency 'Add to Cart' experience globally while treating rare overselling as a solvable business problem (refunds/vouchers) rather than a technical one requir...

#2 B · Reservation-Based Sequential Consistency: Use a lightweight distributed lock or 'intent-to-buy' reservation that expires after 10 minutes. This moves the consistency check to the 'Add to Cart' stage rather than the final checkout, providing a smoother final payment experience at the cost of higher upfront coordination complexity. 1536 dims

Given the emphasis on preventing 'ghost sales' while maintaining fast 'Add to Cart' latency, the reservation-based model directly addresses the root cause by front-loading consistency checks at intent time rather than checkout, avoiding both the high-latency g...

#3 B · Reservation-Based Sequential Consistency: Use a lightweight distributed lock or 'intent-to-buy' reservation that expires after 10 minutes. This moves the consistency check to the 'Add to Cart' stage rather than the final checkout, providing a smoother final payment experience at the cost of higher upfront coordination complexity. 1536 dims

Given the explicit requirement to prevent 'ghost sales' while maintaining fast 'Add to Cart' speed, the platform prioritizes correctness of stock counts over pure availability, ruling out AP-style eventual consistency and quorum-based approximations. Strict gl...

#4 E · Eventual Consistency with Compensating Actions (AP): Prioritize availability and low latency by allowing local writes. Inventory counts may temporarily drift between regions. Over-selling is handled asynchronously via automated 'Order Canceled - Out of Stock' notifications and customer credit vouchers. 1536 dims

Given the priority on fast 'Add to Cart' actions and avoiding heavy distributed locks, the platform favors availability over strict consistency, accepting occasional overselling as a manageable trade-off. Eventual consistency with automated compensating action...

#5 E · Eventual Consistency with Compensating Actions (AP): Prioritize availability and low latency by allowing local writes. Inventory counts may temporarily drift between regions. Over-selling is handled asynchronously via automated 'Order Canceled - Out of Stock' notifications and customer credit vouchers. 1536 dims

Eventual consistency (AP) directly addresses the stated priorities: minimizing latency for 'Add to Cart' actions and tolerating network partitions, while accepting occasional overselling as a manageable business cost through automated compensation (cancellatio...

#6 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

Strict CP consensus (C) directly satisfies the stated goal of preventing ghost sales at all costs, aligning with the priority of correctness over latency in inventory writes. Options like E, D, or B trade off consistency for speed, which risks over-selling — c...

#7 B · Reservation-Based Sequential Consistency: Use a lightweight distributed lock or 'intent-to-buy' reservation that expires after 10 minutes. This moves the consistency check to the 'Add to Cart' stage rather than the final checkout, providing a smoother final payment experience at the cost of higher upfront coordination complexity. 1536 dims

The core requirement is preventing 'ghost sales' (over-selling) while keeping the fast, low-latency user experience of 'Add to Cart' actions—this points toward a CP-oriented model, but strict global consensus (C) sacrifices too much latency/availability during...

GPT 5.4 mini openai_compatible · openai/gpt-5.4-mini
#0 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The key requirement is to prevent ghost sales in a critical inventory system, even under partition risk. That favors a strongly consistent approach where writes are coordinated globally so stock cannot be oversold, even though latency increases. Among the opti...

#1 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The goal is to prevent ghost sales, which requires a consistency model that never allows conflicting inventory writes across regions. Option (C) provides strict strong consistency using global consensus, ensuring no over-selling even under partition risk, thou...

#2 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To prevent ghost sales, the inventory system needs a consistency model that guarantees no over-selling even under partition risk. The option that directly provides this is strict strong consistency with global consensus, since every write is coordinated before...

#3 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The key requirement is to prevent ghost sales, which means the inventory system cannot tolerate conflicting writes or stale stock reads that could oversell items. Since the prompt emphasizes significant partition risk and explicitly asks for a consistency mode...

#4 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The key requirement is to prevent ghost sales, which means the inventory system must never allow conflicting writes that could oversell stock. In a multi-region setup with partition risks, the safest choice is a globally coordinated consistency model that sacr...

#5 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The key requirement is to prevent ghost sales, which means the inventory system cannot allow conflicting writes during partitions. Among the choices, strict strong consistency is the only model that guarantees no over-selling by requiring global agreement befo...

#6 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The key requirement is to prevent ghost sales, even under significant network partition risk, so the inventory system must favor correctness over availability. That points to a strongly consistent, globally coordinated approach rather than eventual consistency...

#7 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

The key requirement is to prevent ghost sales, which means the inventory system must never allow conflicting writes that could oversell stock. Given the high risk of network partitions, the safest choice is a strongly consistent, globally coordinated database,...

Gemini 3 Flash Preview openai_compatible · google/gemini-3-flash-preview
#0 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To maximize user experience while preventing 'ghost sales,' the system must prioritize consistency over availability during network partitions (CAP theorem). Strict Strong Consistency (C) ensures that every 'Add to Cart' or 'Checkout' action reflects the true ...

#1 B · Reservation-Based Sequential Consistency: Use a lightweight distributed lock or 'intent-to-buy' reservation that expires after 10 minutes. This moves the consistency check to the 'Add to Cart' stage rather than the final checkout, providing a smoother final payment experience at the cost of higher upfront coordination complexity. 1536 dims

To prevent "ghost sales" (selling out-of-stock items) while managing network partition risks, a system must prioritize consistency over availability (CP) or use a coordination mechanism. Option (C) provides a globally ordered state that guarantees zero over-se...

#2 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To prevent "ghost sales" (overselling) while managing global network partition risks, a system must prioritize consistency over availability in the CAP theorem. Option (C) provides a Strict Strong Consistency model through distributed consensus, ensuring that ...

#3 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To prevent "ghost sales" (overselling) while managing the risks of network partitions, the system must prioritize consistency over availability for the inventory data (CAP theorem's CP). Option (C) ensures that every transaction is globally synchronized via a ...

#4 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To prevent "ghost sales" (over-selling) in a multi-region deployment, the system must prioritize consistency over availability during network partitions. **Option (C)** utilizes a globally distributed consensus protocol to ensure a single, accurate view of inv...

#5 A · Inventory Partitioning (Siloed Allocation): Divvy the total stock into fixed pools assigned to specific geographic regions. A user in Europe only sees inventory allocated to Europe. If a region runs out, it must request a manual 'rebalance' from another region's pool, adding operational overhead but ensuring local consistency. 1536 dims

To prevent "ghost sales" (selling out-of-stock items) while managing multi-region latency, a trade-off between strict consistency and system availability is required. Option (A) ensures local consistency by siloing inventory, which prevents over-selling and mi...

#6 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To prevent 'ghost sales' (selling out-of-stock items) while managing network partition risks, a system must prioritize consistency over availability (CP) in accordance with the CAP theorem. Option (C) ensures a single global truth for inventory levels through ...

#7 C · Strict Strong Consistency (CP): Use a globally distributed consensus protocol (like Spanner or CockroachDB) for all inventory writes. This ensures no over-selling occurs, accepting increased latency for writes during cross-region synchronization and potential downtime during network partitions. 1536 dims

To prevent 'ghost sales' (selling out-of-stock items) while ensuring a smooth experience, the system must prioritize consistency over availability during network partitions. Option (C) ensures a single global truth for inventory levels via a distributed consen...

Timings

Stages

Sampling6233 ms
Embedding637 ms
Signals10 ms
PPV1 ms

Errors

Agent and Round Errors

No errors recorded.