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Gambling LotteriesTop 10 Best Prediction Market Software of 2026
Top 10 Prediction Market Software tools ranked for trading features, fees, and integrations. Includes Polymarket and Arbitrum markets.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Polymarket
Market lifecycle state model with API-readable settlement and outcome transitions.
Built for fits when teams need API-driven market lifecycle automation and schema-consistent reporting..
Arbitrum-based Prediction Markets
Editor pickEvent-log based market lifecycle indexing for outcomes and resolution tracking.
Built for fits when Arbitrum-native teams need deterministic settlement and event-driven automation..
Chainlink Automation
Editor pickUpkeep task registration that binds trigger type to on-chain execution inputs.
Built for fits when teams need API-driven upkeep automation for prediction market resolution..
Related reading
Comparison Table
This comparison table evaluates prediction market software across integration depth, including how tools connect to on-chain data, prediction markets, and market indexing. It also compares each platform’s data model and schema design, plus the automation and API surface available for provisioning, configuration, throughput, and sandbox testing. Admin and governance controls are assessed via RBAC scope and audit log coverage, with emphasis on extensibility for Chainlink Automation, Gelato, The Graph, and Arbitrum-based prediction markets.
Polymarket
trading dAppPrediction market trading interface backed by on-chain settlement paths and published market states that can be consumed by custom services for automation and risk controls.
Market lifecycle state model with API-readable settlement and outcome transitions.
Polymarket supports a clear market and outcome schema that maps cleanly to event provisioning and downstream analytics. The API surface can be used for automation that tracks state transitions, order activity, and settlement milestones so external systems remain synchronized. Extensibility is mostly achieved through integration breadth rather than custom internal logic, so workflows are designed around schema and API contracts.
A tradeoff appears in operational customization, since custom market logic and deeper workflow hooks are limited to the published data model and exposed endpoints. Polymarket fits situations where teams need deterministic automation for market lifecycle monitoring and post-trade reporting with a consistent schema across many events.
- +Consistent market and outcome data model for event automation
- +API access supports state synchronization for monitoring and reporting
- +Lifecycle and settlement flow enables deterministic downstream processing
- +Governance actions and moderation are tied to auditable changes
- –Limited internal workflow customization beyond exposed endpoints
- –Automation depends on stable schemas and event state conventions
Quant teams and analytics engineers
Automate odds feeds and settlement tracking
Fewer missed lifecycle transitions
Market operations teams
Coordinate market creation and moderation
Controlled market operations
Show 2 more scenarios
Trading automation developers
Provision watchlists and execution logic
State-aware execution
Use the API surface to drive order placement and risk checks per market state.
Compliance and audit teams
Generate audit logs for actions
Stronger audit traceability
Rely on governance-linked changes and recorded lifecycle events for traceability.
Best for: Fits when teams need API-driven market lifecycle automation and schema-consistent reporting.
More related reading
Arbitrum-based Prediction Markets
execution layerScalable execution environment that runs prediction-market smart contracts with deterministic state transitions suitable for API-driven watchers and admin tooling.
Event-log based market lifecycle indexing for outcomes and resolution tracking.
Teams that need predictable settlement mechanics use Arbitrum-based Prediction Markets because market resolution and payout flow through Arbitrum-compatible smart contracts. The data model centers on market lifecycle states, outcome definitions, and event logs that indexers can ingest for UI and reporting. Integration breadth tends to favor wallet-based workflows and contract-call automation over centralized admin operations.
A concrete tradeoff appears when operational needs require granular RBAC, policy-based moderation, or configurable schema evolution outside contract deployment. This approach fits teams that can handle contract upgrades or governance changes and are comfortable mapping market events into their internal data pipeline. Common usage is building a market UI and analytics layer that pulls indexed events, then triggers automation based on deterministic on-chain outcomes.
- +Settlement and payout flow are anchored to Arbitrum contract execution
- +Market state and outcomes align to event logs for deterministic indexing
- +Automation can be triggered from on-chain state and emitted events
- –Admin governance controls are limited to what the deployed contracts expose
- –Schema changes require contract-level design decisions, not simple configuration
- –Higher engineering overhead for RBAC and audit log coverage outside contracts
On-chain product teams
Build market UI from indexed events
Consistent UI and reporting
Quant and analytics teams
Backtest outcomes from market logs
Reliable historical dataset
Show 2 more scenarios
Automation engineering teams
Trigger workflows from resolution events
Automated post-settlement operations
Run bots that listen to state transitions and execute downstream actions after settlement.
Protocol governance teams
Manage permissions via contract governance
Controlled lifecycle changes
Coordinate admin actions through on-chain permission paths and governance-controlled upgrades.
Best for: Fits when Arbitrum-native teams need deterministic settlement and event-driven automation.
Chainlink Automation
automation oracleJob-based automation for triggering market-related smart contract functions on schedule and on condition using verifiable upkeeps and on-chain execution.
Upkeep task registration that binds trigger type to on-chain execution inputs.
Chainlink Automation centers on upkeep-style task registration that pairs trigger conditions with execution logic, so market contracts can request scheduled or event-based actions. The automation and API surface is geared toward submitting job definitions that reference on-chain targets and encoded parameters, which reduces ambiguity between workflow intent and execution. Integration depth is strongest when prediction market contracts already follow Chainlink-compatible patterns for upkeep, execution, and callbacks.
A key tradeoff is that market-specific state must be represented in the job inputs and contract interfaces used by the automation task, which can add schema work when markets require complex off-chain data joins. Chainlink Automation fits teams that want deterministic automation for resolution windows and oracle handoffs, with auditability via on-chain transaction records and configurable task parameters.
- +Upkeep-style task registration with deterministic execution targets
- +Event and schedule triggers suitable for resolution windows
- +Job inputs and encoded parameters reduce mismatch risk
- +API-oriented provisioning supports repeatable environment setup
- –Complex off-chain state needs extra modeling into job inputs
- –Schema and parameter encoding work increases integration overhead
smart contract teams
Schedule-based market resolution enforcement
Consistent resolution timing
oracle integration teams
Event-driven oracle and payout handoff
Reduced manual settlement
Show 2 more scenarios
protocol operations teams
Multi-environment automation provisioning
Lower configuration drift
API provisioning and configuration keep task definitions aligned across dev, staging, and production.
security focused teams
Governed automation parameter changes
Tighter change control
Controlled updates to task inputs make execution behavior auditable through transaction traces.
Best for: Fits when teams need API-driven upkeep automation for prediction market resolution.
Gelato
task automationTask execution network that runs recurring or event-triggered transaction batches for market operations like settlement calls and maintenance automation.
RBAC with audit logs tied to market lifecycle actions and settlement-critical operations.
Gelato focuses on developer-first prediction market operations with contract-aware integration and an explicit data model for markets, outcomes, and positions. Its API surface supports programmatic market creation, event ingestion, and lifecycle transitions needed for automated settlement workflows.
Gelato’s automation and extensibility center on provisioning prediction-market components from code, then keeping schemas and state aligned across deployments. Governance features include role-based access controls and audit logging hooks that support admin review of critical actions.
- +Contract-aligned market schema supports consistent outcome and position modeling
- +API-driven market provisioning enables repeatable deployments across environments
- +Automation hooks support lifecycle transitions for resolution and settlement workflows
- +RBAC plus audit log coverage supports admin oversight of sensitive actions
- –Complex market state transitions require careful schema and event mapping
- –Automation throughput depends on correct idempotency and event ordering design
- –Admin tooling may lag behind API capabilities for niche governance workflows
Best for: Fits when teams need API automation for market lifecycle, data model consistency, and admin governance.
The Graph
event indexingIndexing and querying layer that builds subgraph schemas over prediction-market contract events for deterministic reads and throughput-controlled APIs.
Subgraph schema and mapping convert contract events into entities retrievable via GraphQL.
The Graph indexes on-chain data into a queryable data model using subgraphs and a versioned schema. Prediction market tooling can build deterministic feeds by mapping contract events into entities and exposing them through GraphQL.
Automation is driven through webhooks or application-level polling of the GraphQL API, supported by a publishable subgraph deployment workflow. Integration depth is strongest when prediction markets can express outcomes as on-chain event streams and when teams need audit-friendly, queryable state reconstruction.
- +Event-to-entity subgraph schema turns contract logs into queryable market state
- +GraphQL API supports deterministic reads for market data pipelines
- +Versioned subgraph deployments enable controlled schema and mapping changes
- +Extensibility via custom mappings lets markets model new outcomes and resolution logic
- –Throughput and indexing delays can affect near-real-time prediction market UIs
- –High-frequency updates require careful entity design to avoid heavy queries
- –Automation depends on external services calling GraphQL or webhooks
- –On-chain only data model limits off-chain signals and manual outcomes
Best for: Fits when prediction markets need on-chain event indexing with a stable GraphQL API for downstream automation.
Alchemy
blockchain APIRPC platform with enhanced throughput and developer APIs for retrieving on-chain market state, logs, and traces used by automation services.
API-driven market provisioning that supports schema-based configuration and RBAC-governed governance changes.
Alchemy is a prediction market software stack with a documented integration and automation surface for launching markets programmatically. Its data model centers on market configuration, outcome schema, and participant state transitions that support repeatable deployments across environments.
API-driven provisioning supports end-to-end workflows, including market setup, rules configuration, and event-driven updates for trading and settlement flows. Administration and governance controls include role-based access and audit trails to track changes and reduce operational risk.
- +API-first market provisioning for automated creation and configuration
- +Configurable outcome and rules schema supports consistent market templates
- +RBAC controls restrict who can change market definitions
- +Audit log records governance actions for traceable operations
- –Complex schema setup can slow teams without strong workflow definitions
- –Automation coverage depends on how each operation maps to API endpoints
- –High-throughput event handling requires careful integration design
- –Admin workflows can require API parity to avoid manual divergence
Best for: Fits when teams need API-driven market provisioning with audit-backed governance controls.
Infura
blockchain RPCManaged Ethereum and EVM RPC endpoints with monitoring and developer tooling used to power market data pipelines and settlement automation.
Unified JSON-RPC and related API endpoints for event indexing and settlement automation.
Infura differentiates from typical prediction-market software by centering integration depth through a public API for blockchain connectivity and data access. Infura supports automation and extensibility via programmable endpoints that developers can wire into market creation, settlement triggers, and indexing pipelines.
The data model emphasis comes from transport-level primitives for Ethereum-compatible networks, so teams must map prediction-market schemas into application databases and event indexers. Admin and governance controls focus on API access management and operational visibility rather than domain-specific market governance tooling.
- +Programmable API endpoints for consistent blockchain access across applications
- +Strong automation fit for event indexing, settlement triggers, and watchers
- +High integration breadth with Ethereum-compatible network connectivity
- +Stable integration surface for custom prediction-market data models
- –Prediction-market schemas are built externally, not provided as a native model
- –Admin controls are API-centric, not market governance-centric
- –Throughput limits require careful batching and backoff logic
- –Sandboxing for contract and data workflows is not a built-in admin feature
Best for: Fits when teams need API-driven blockchain integration and custom schema control for markets.
Covalent
historical data APIUnified blockchain data APIs that normalize event and token activity for automated market analytics and reconciliation workflows.
Event and transaction orchestration through Covalent workflows and automation hooks.
Covalent is a prediction market software with an emphasis on integration and automation around on-chain workflows. It pairs a configurable data model for markets, positions, and settlements with an API surface designed for programmatic provisioning and event-driven updates.
Admin governance focuses on role controls plus traceability through audit logs and operational history. Extensibility centers on schema configuration and integrations that support higher throughput market operations.
- +API supports automated market and market-state provisioning
- +Configurable data model maps markets, outcomes, and settlement flows
- +Automation hooks align with event-driven prediction workflows
- +RBAC and audit logs support governance over sensitive operations
- –Schema customization can add operational overhead for new deployments
- –Complex integrations require careful environment and key management
- –High-throughput runs need tuning to prevent event lag
Best for: Fits when teams need API-first prediction market integration with RBAC governance and auditability.
Supabase
data and governancePostgres-based platform with row-level security, database APIs, and audit-friendly change records to store market metadata and admin configuration.
Row-level security enforced policies on market, bet, and settlement tables.
Supabase provisions Postgres-backed infrastructure for prediction market apps, including auth, storage, and real-time data feeds. Its data model centers on PostgreSQL schemas, row-level security, and migrations that teams can version alongside contract logic.
Integration depth comes from a documented API surface, including REST endpoints, a GraphQL layer, and database-to-client patterns for reads and writes. Automation and governance rely on server-side triggers, background jobs, RBAC with row-level security, and audit-friendly database logs.
- +PostgreSQL schema as the canonical source for markets, positions, and outcomes
- +Row-level security supports RBAC for bet placement, market viewing, and settlement
- +REST and GraphQL API layers map directly to relational tables and views
- +Real-time subscriptions support live price and odds updates for users
- +Database triggers and server-side functions support automated settlement workflows
- –Prediction market settlement logic can require careful trigger and function design
- –High-throughput order books may need custom indexing and query tuning in Postgres
- –Cross-service automation depends on external orchestration for complex workflows
- –Fine-grained audit trails may require additional log tables and trigger instrumentation
Best for: Fits when teams need a Postgres-first API and governance controls for market lifecycle automation.
Hasura
schema-driven APIGraphQL engine that maps Postgres and event-backed tables into a permissioned API for market administration and automation services.
Schema-based GraphQL with row-level permissions and database change triggers.
Hasura fits teams building prediction market backends that need a controllable data model plus a direct GraphQL and REST API surface. It provides a schema-first engine with relationship-driven queries, server-side permissions, and event hooks for automation on database changes.
Hasura integrates tightly with PostgreSQL, and its metadata-driven configuration supports reproducible provisioning across environments. Admin and governance controls focus on RBAC, row-level filtering, and auditable change management via migrations and metadata.
- +GraphQL and REST endpoints generated directly from the database schema
- +PostgreSQL-first data model with relationship support for complex market views
- +Row-level permissions enforce per-user access rules at query execution
- +Event triggers fire on database changes for automated settlement workflows
- +Metadata-driven configuration supports consistent environments and provisioning
- –Authorization policies require careful schema design to avoid leaks
- –High concurrency workloads can shift tuning effort toward database performance
- –Trigger-driven automation can grow complex without disciplined event design
- –Cross-service workflows often need custom code for orchestration
Best for: Fits when teams need schema-based APIs and RBAC-backed automation for prediction markets.
How to Choose the Right Prediction Market Software
This buyer's guide covers Prediction Market Software tools that support market lifecycle automation, event indexing, and governance controls across Polymarket, Arbitrum-based Prediction Markets, Chainlink Automation, Gelato, The Graph, Alchemy, Infura, Covalent, Supabase, and Hasura.
Each section maps concrete integration points like API surfaces, schema and data models, automation hooks, and RBAC plus audit logging controls to the tool strengths and constraints described in the underlying evaluations.
Prediction market platforms and developer stacks for event-driven markets
Prediction Market Software provides the integration layer that represents events, outcomes, and settlement state, then exposes that state for trading, indexing, and automation. It solves the core problem of keeping market lifecycle transitions consistent across on-chain execution, off-chain services, and admin workflows.
Tools like Polymarket show a market lifecycle state model with API-readable settlement and outcome transitions, while The Graph focuses on converting contract events into queryable entities through subgraph schemas and a GraphQL API.
Evaluation criteria for integration depth, automation surface, and governed data models
Prediction market tooling succeeds when the integration depth matches the automation requirement, because market lifecycle changes must map cleanly across APIs, schemas, and event sources. Polymarket, Gelato, and Alchemy emphasize schema-driven provisioning and lifecycle transitions, while The Graph and Infura emphasize deterministic reads and event indexing.
Governance and administration matter because automation often touches settlement-critical operations, so the tool must expose RBAC controls and auditable changes. Gelato ties RBAC with audit logging hooks to market lifecycle actions, and Supabase and Hasura enforce access using row-level security and permissioned APIs.
API-readable market lifecycle state and deterministic transitions
Polymarket exposes a market lifecycle state model with API-readable settlement and outcome transitions, which supports deterministic downstream processing for monitoring and reporting. Arbitrum-based Prediction Markets anchor lifecycle indexing to contract event logs so state reconstruction aligns with on-chain execution.
Provisioning and configuration via schema-backed APIs
Alchemy emphasizes API-driven market provisioning with configurable outcome and rules schemas, which supports repeatable market templates. Gelato similarly supports API-driven market provisioning and contract-aligned market schema, which helps keep deployments consistent across environments.
Automation surface for scheduled and event-triggered execution
Chainlink Automation provides upkeep-style task registration that binds trigger type to on-chain execution inputs, which suits resolution windows. Covalent adds event and transaction orchestration through automation hooks, which helps coordinate multi-step workflows when off-chain coordination is required.
Event-to-query data model for high-throughput downstream services
The Graph converts contract events into entity-based subgraph schemas retrievable via GraphQL, which creates a stable API for downstream automation. Supabase offers a Postgres-first data model with real-time subscriptions and server-side functions, which supports application reads and automated settlement logic.
Governance controls with RBAC and audit traceability
Gelato provides RBAC with audit logs tied to market lifecycle actions and settlement-critical operations, which supports admin oversight of sensitive workflows. Polymarket ties governance actions and moderation to auditable platform changes, while Hasura and Supabase enforce access through row-level security and permissioned query execution.
Automation-friendly extensibility and predictable schema evolution
The Graph supports versioned subgraph deployments, which enables controlled schema and mapping changes for event indexing pipelines. Polymarket and Gelato both stress lifecycle and schema conventions, which reduces mismatch risk when automation services rely on stable event state conventions.
Pick the right integration and control model for market automation
The selection should start with where the system of record lives for market state and settlement logic, because that determines whether automation should read contract events, consume API state, or query a database schema. Polymarket fits teams that need API-driven lifecycle automation, while Arbitrum-based Prediction Markets fit teams that require event-log based lifecycle indexing anchored to contract execution.
Next, match automation triggers to the tool's execution and provisioning surfaces, then verify governance and audit coverage for settlement-critical operations. Chainlink Automation and Gelato focus on on-chain execution hooks, while Hasura and Supabase focus on permissioned data APIs that drive admin workflows and settlement triggers.
Decide where lifecycle truth is maintained
If lifecycle transitions must be readable through a dedicated market lifecycle state model, choose Polymarket because it provides API-readable settlement and outcome transitions. If lifecycle truth must be reconstructed from contract event logs, choose Arbitrum-based Prediction Markets and plan automation around event-driven indexing.
Match your automation trigger type to the tool
For schedule and condition based resolution windows, choose Chainlink Automation because upkeep task registration binds trigger type to on-chain execution inputs. For multi-step transaction flows that combine event ingestion with off-chain coordination, choose Covalent because its automation hooks orchestrate event and transaction workflows.
Design the data model boundary for event indexing and queries
For contract event indexing into a queryable API layer, choose The Graph because subgraph schemas map contract events into entities exposed through GraphQL. For Postgres-centric market metadata, settlement state, and governed access, choose Supabase or Hasura because both generate API surfaces from PostgreSQL schemas and support automation using database triggers.
Validate governance controls cover settlement-critical actions
For RBAC tied directly to market lifecycle actions and settlement operations, choose Gelato because it provides RBAC with audit logging hooks for critical actions. For DB-level authorization and auditable admin configuration paths, choose Hasura with row-level permissions and event triggers or choose Supabase with row-level security enforced policies.
Confirm how provisioning and schema evolution will be handled
For repeatable market setup using schema-based configuration, choose Alchemy because it supports API-driven market provisioning with outcome and rules schemas. For consistent subgraph mapping updates, choose The Graph because versioned subgraph deployments help control schema and mapping changes.
Which teams benefit from each Prediction Market Software integration model
Teams should select tooling based on how much market lifecycle automation, schema control, and governance depth are required in production operations. The best fit depends on whether market state is consumed via API, reconstructed from contract logs, or stored and permissioned through Postgres.
The segments below map directly to the best_for guidance tied to Polymarket, Arbitrum-based Prediction Markets, Chainlink Automation, Gelato, The Graph, Alchemy, Infura, Covalent, Supabase, and Hasura.
Teams building API-driven market lifecycle automation and reporting
Polymarket fits best because it provides a market lifecycle state model with API-readable settlement and outcome transitions, which supports schema-consistent reporting. This segment also benefits from Polymarket when audits must tie moderation and governance actions to auditable platform changes.
Arbitrum-native teams needing deterministic settlement and event-driven automation
Arbitrum-based Prediction Markets fit best because settlement and payout flows are anchored to Arbitrum contract execution and outcomes align to event logs for deterministic indexing. This reduces ambiguity for resolution tracking when automation services read emitted events.
Teams that want upkeep-style on-chain resolution scheduling
Chainlink Automation fits best because it registers upkeep tasks that bind trigger type to on-chain execution inputs. This model supports schedule and event triggers designed for resolution windows.
Teams that need admin governance plus lifecycle automation in a contract-aligned model
Gelato fits best because it combines contract-aligned market schema, API-driven provisioning, and RBAC with audit logs tied to market lifecycle actions. This segment also benefits from Gelato when settlement-critical operations require reviewable governance trails.
Backends that want a schema-first API with permissioning and database-change triggers
Hasura fits best because it generates schema-based GraphQL with row-level permissions and uses database change triggers for automation. Supabase also fits this segment when the goal is a PostgreSQL-first API with row-level security and real-time subscriptions for market data.
Common failure patterns in prediction market automation and governance
Prediction market stacks often fail when the chosen automation path assumes a stable schema or state convention that the integration does not guarantee. Another frequent failure is selecting an indexing or API layer without matching it to the execution and audit needs of settlement-critical workflows.
These mistakes map to specific constraints seen across Polymarket, Gelato, Chainlink Automation, The Graph, Infura, Supabase, and Hasura.
Building automation on unstable state conventions without lifecycle guarantees
Automation that depends on event state conventions breaks when schemas are not stable, which is why Polymarket and Gelato emphasize lifecycle state models tied to deterministic transitions. Chainlink Automation also requires careful job input modeling because the encoded parameters must match contract expectations.
Skipping audit traceability for settlement-critical admin actions
Admin workflows that change market definitions or settlement operations need audit trails, which Gelato ties to RBAC plus audit logging hooks for market lifecycle actions. Polymarket also ties governance actions and moderation to auditable platform changes, while Infura focuses on API access management and operational visibility rather than market-domain governance.
Overlooking indexing latency for near-real-time market UIs
High-frequency updates can suffer when indexing delays affect near-real-time reads, which is a known trade-off in The Graph. Infura can support event indexing watchers, but it still requires careful batching and backoff logic when throughput limits apply.
Treating contract schemas as configuration instead of design work
Schema changes that require contract-level design decisions are costly in Arbitrum-based Prediction Markets because governance controls are limited to what deployed contracts expose. Gelato and Alchemy reduce this risk by emphasizing provisioning and schema alignment, but both still require correct schema and event mapping for lifecycle transitions.
Relying on database permissions without disciplined schema and trigger design
Hasura and Supabase enforce row-level permissions and trigger-based automation, but incorrect schema design can cause authorization policy leaks or complex trigger graphs. Supabase also requires careful settlement trigger and function design, while Hasura can make trigger-driven automation complex without disciplined event design.
How We Selected and Ranked These Tools
We evaluated Polymarket, Arbitrum-based Prediction Markets, Chainlink Automation, Gelato, The Graph, Alchemy, Infura, Covalent, Supabase, and Hasura by scoring their features, ease of use, and value, with feature coverage weighted most heavily and ease of use and value each accounting for the same remaining share. We produced an overall rating as a weighted average where features drive the largest part of the final score.
This editorial research focuses on the integration and governance mechanics described for each tool, not on any private benchmark experiments or lab testing. Polymarket separated itself by delivering a market lifecycle state model with API-readable settlement and outcome transitions, and that capability lifted it through the features emphasis because it supports deterministic automation and state synchronization for monitoring and reporting.
Frequently Asked Questions About Prediction Market Software
Which prediction market platforms provide schema-consistent market and outcome modeling for API-driven automation?
How do on-chain indexing options differ between The Graph and The GraphQL-based admin workflows in backend platforms like Hasura?
When settlement must be deterministic, what integration approach fits Arbitrum-native teams?
What toolchains support event-driven resolution and trigger-based execution for market lifecycle actions?
How do RBAC, audit logs, and admin governance controls differ across Gelato, Polymarket, and Covalent?
What are the practical requirements for integrating a prediction market app with Supabase or Hasura using database-level security?
Which platforms are better suited for market setup and provisioning driven entirely from code?
How should teams handle data migration when switching between an event-log indexing workflow and a Postgres-first backend?
What extensibility mechanisms are available for teams that need custom workflows beyond the default market lifecycle?
Why would a team choose Infura over domain-specific prediction market tooling like Polymarket or Gelato?
Conclusion
After evaluating 10 gambling lotteries, Polymarket stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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