AIGQLUnify isn’t a database GraphQL engine like Hasura; it’s built to solve a different class of problems at the API fabric layer.
Hasura and other database-centric GraphQL platforms are excellent when the main challenge is giving developers GraphQL over relational data. AIGQLUnify focuses on something else: stitching together REST-heavy, multi-IdP, policy-constrained estates into a zero-trust federated API fabric with PDP, DSAR, and observability in the path.
Deep-dive: where AIGQLUnify sits in the landscape
AIGQLUnify is a zero-trust, policy-aware API fabric that starts from REST/OpenAPI and enforces PDP/PEP per field at runtime. This page mirrors the PDF-style landscape and side-by-side matrix, and shows how AIGQLUnify sits alongside Apollo, database-centric GraphQL engines, gateways, and stitching libraries.
Side-by-side matrix
A quick matrix across deployment, federation, policy, DSAR, and observability. Capabilities reflect typical deployments and public docs; many vendors offer enterprise add-ons or integrations to fill gaps.
| Criteria | AIGQLUnify | Apollo GraphOS | DB-centric GraphQL (e.g., Hasura) |
StepZen | Kong/Tyk | GraphQL Mesh | Grafbase |
|---|---|---|---|---|---|---|---|
| Deployment models | SaaS, self-host, hybrid | SaaS, hybrid | Self-host, Cloud | SaaS | Self-host, Cloud | DIY (library) | SaaS |
| Starts from REST/OpenAPI | Yes | Via resolvers | Connectors | Yes | Plugins | Yes (library) | Connectors |
| Requires DB/service code access | No | Service code | DB/metadata | Gateway config | Plugins/policies | Your code | Project config |
| Apollo-compatible federation | Yes | Yes | Gateway options | Partial | Stitching modes | Stitching | Limited |
| PDP/PEP per-field at runtime | Yes | Edge/policy extensions | Row/column rules | No | No | No | No |
| Field-level masking | Yes | External/plugins | Columns/rules | No | Plugin-level | No | Rules/features |
| Identity propagation end-to-end | Yes | Good | Good | Good | Edge focus | DIY | Good |
| DSAR/Audit workflows | Yes | Not native | Limited | No | No | No | No |
| Observability (OTel/Jaeger) | Yes | Studio/OTel | Integrations | Some | Yes | DIY | Some |
| SIEM/SOAR hooks | Yes | Via integrations | Via webhooks | No | Yes | DIY | No |
| Networking: mTLS / egress allowlists | Yes | Enterprise add-ons | Enterprise add-ons | Unknown | Yes | DIY | Unknown |
| Pricing posture | Usage + tier | Usage + seats | Tiered + nodes | Usage | Enterprise licensing | n/a | Usage |
| Enterprise add-ons (SAML/SCIM, VPC, KMS) | Yes | SAML/VPC add-ons | SAML/VPC/KMS | SAML (SaaS) | Enterprise plugins | n/a | SaaS |
| Caching strategy | Server-side projection | Router/cache features | Row-level caching | Gateway cache | Gateway cache | App-level | Edge cache |
| Schema hot-reload / plan publish | Plan publish → DP | Router config deploy | Metadata apply | Push schema | Gateway reload | App reload | Push schema |
| Router support / composition | Yes | Yes | Partial | Partial | Gateway | n/a | Partial |
| SLA / Support tiers | Gold/Enterprise | Premier | Enterprise | Enterprise | Enterprise | Community | Pro |
Capabilities reflect typical deployments and public docs; many vendors offer enterprise add-ons or partner integrations to fill gaps. This is a fit overview, not an exhaustive feature checklist.
Database-centric GraphQL vs AIGQLUnify at the API fabric layer
This is not “we are better.” It’s fit. Database GraphQL engines shine when you mostly need GraphQL over a few well-owned databases. AIGQLUnify shows up when the estate is mixed: REST, SOAP, warehouses, multiple IdPs, DSAR obligations, and AI that must not bypass policy.
| Dimension | Database-centric GraphQL engines (e.g., Hasura) |
AIGQLUnify (zero-trust API fabric) |
|---|---|---|
| Primary focus | GraphQL over relational databases (Postgres, MySQL, etc.). | Federated API fabric across REST, SOAP, subgraphs, IdPs, PDP, and DSAR. |
| Source of truth | Database schema and tables. | OpenAPI specs, REST endpoints, IdP mappings, PDP policy, and DSAR metadata. |
| Estate assumptions | Relatively clean schema ownership; strong DB control. | Messy enterprise reality: many services, multiple IdPs, legacy APIs, regulated data. |
| Policy integration | Typically implemented via auth rules, RLS, and custom resolvers. | PDP/PEP in the path. Decisions use { subject, action, resource, context } with field-level obligations and masking. |
| DSAR / privacy | Usually handled in separate workflows or services. | DSAR lifecycle APIs (create/export/delete) and audit artefacts are built into the control plane and exposed via the fabric. |
| AI posture | LLM usage patterns vary per team; not inherently policy-aware. | AI helpers are explicitly toggled by PDP (features.ai) and only see masked, policy-approved graph views. |
| Runtime location & latency | Close to the database; minimal network hops; great as a northbound DB API. | At the API edge in front of REST/legacy services, with PDP, DSAR, and OTEL in the path. Tuned to keep added latency bounded and observable. |
| Best placement in architecture | As a database GraphQL layer feeding services or AIGQLUnify. | As the federated edge and policy fabric, fronting REST, legacy APIs, and even Hasura itself as a subgraph/source. |
Quick mental model
Think of Hasura as “GraphQL over Postgres” and AIGQLUnify as “zero-trust API fabric over everything”.
In many estates you’ll want both: Hasura close to the DB for low-latency table access, and AIGQLUnify at the edge for multi-service federation, PDP/PEP, DSAR, and policy-aware AI.
When a database GraphQL engine is the right tool
Your main pain is SQL ↔ GraphQL.
You want developers to stop hand-writing REST handlers over a few relational databases and just query tables via GraphQL.
Governance is still light.
You’re not yet under heavy DSAR, field-level masking, or multi-IdP pressure. A thin DB API layer is “good enough” for now.
Latency budget is razor-thin.
You’re building something very latency-sensitive that mostly talks to one or two databases directly and can’t afford another hop.
When AIGQLUnify is the right tool
You have many REST and legacy services.
Your real bottleneck isn’t “no GraphQL over Postgres,” it’s “15+ REST and legacy services that all implement auth differently and nobody agrees who owns which field.”
You have strong governance pressure.
You need field-level masking, DSAR exports/deletes, and SIEM events you can show auditors — without building a separate governance product.
You want AI, but not a backdoor.
You want NL → GraphQL, schema hints and join suggestions, but you are not willing to let a model bypass PDP or talk to raw databases outside the federated fabric.
Use them together.
Many teams will keep Hasura (or similar) close to their databases and put AIGQLUnify at the federated edge in front of the broader REST + policy + DSAR universe. AIGQLUnify can treat Hasura itself as just another subgraph or REST/GraphQL source, while still applying PDP obligations, DSAR workflows, and telemetry at the edge.