graphql-engine vs apijson
Two of the top projects in Backends and databases, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
graphql-engine
GraphQL API layer over Postgres, MongoDB, ClickHouse and SQL Server
apijson
Java ORM that exposes CRUD APIs over JSON requests without per-endpoint code
Verdict
graphql-engine ranks higher, 65 to 46. Of the 5 score parts we measure for both, graphql-engine leads on 3, apijson on 1 and 1 is even.
- Adoptiongraphql-engine leads by 43 points, 67 to 24: a wide gap.
- FreshnessEven at 100.
- Maintenanceapijson leads by 9 points, 90 to 81.
- Easy to rungraphql-engine leads by 33 points, 33 to 0: a wide gap.
- Agent-readygraphql-engine leads by 30 points, 30 to 0: a wide gap.
Pick graphql-engine if you are
Teams exposing existing databases as a GraphQL API for apps
- Supports PostgreSQL, MongoDB, ClickHouse and MS SQL Server as data sources
- Connector SDKs in TypeScript, Python and Go for custom logic
Pick apijson if you are
Java backend developers who want codeless CRUD APIs over SQL or NoSQL databases
- One JSON request can query several related tables, replacing multiple endpoint calls
- Many data sources listed: MySQL, PostgreSQL, Oracle, SQL Server, ClickHouse, Redis, Kafka, Elasticsearch
| What we compare | graphql-engine | apijson |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 67, popular | 24, niche |
| Freshness | 100, active | 100, active |
| Maintenance | 81, healthy | 90, healthy |
| Easy to run | 33, some setup | 0, hard |
| Agent-ready | 30, minimal | 0, none |
| Facts from GitHub and the README | ||
| Stars | 32.1k | 18.4k |
| License | Apache-2.0 (permissive) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Sep 2026 | Oct 2026 |
| Language | TypeScript | Java |
| Docker | Yes | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
graphql-engine
Hasura GraphQL Engine exposes data from PostgreSQL and its flavors, MongoDB, ClickHouse and MS SQL Server through a single GraphQL endpoint. Custom business logic can be added with TypeScript, Python and Go connector SDKs. The repo is a mono-repo holding the V3 engine (which powers Hasura DDN) and the stable V2 engine, with all data connectors open source.
Who it is for: Teams exposing existing databases as a GraphQL API for apps
Strengths
- Supports PostgreSQL, MongoDB, ClickHouse and MS SQL Server as data sources
- Connector SDKs in TypeScript, Python and Go for custom logic
- Core engines and data connectors are Apache-2.0 licensed
- V2 remains available as the current stable version
Weaknesses
- Large mono-repo with long history; README recommends shallow or sparse clones
- V2 and V3 are separate codebases with separate docs
- V3 is documented around the hosted Hasura DDN workflow
- README lists no RAM, port or AI model details
- no GPU
- Compose
- Needs PostgreSQL, MongoDB, ClickHouse, MS SQL Server
apijson
APIJSON is a Java library and JSON-based protocol. Clients send a JSON describing the tables and fields they want, and the server maps it to SQL and returns JSON in the same shape, so backend developers write no per-endpoint CRUD code. It covers reads, writes, fuzzy search and remote function calls, and ships with API docs and test tooling (APIAuto).
Who it is for: Java backend developers who want codeless CRUD APIs over SQL or NoSQL databases
Strengths
- One JSON request can query several related tables, replacing multiple endpoint calls
- Many data sources listed: MySQL, PostgreSQL, Oracle, SQL Server, ClickHouse, Redis, Kafka, Elasticsearch
- Added via Maven or Gradle through JitPack; works with Spring, SpringBoot, JFinal, Nutz
- Community ports listed for Go, C#, PHP, Node.js, Python and Rust
Weaknesses
- Java-centric; non-Java ports are separate third-party repositories with unknown maturity
- License is reported as NOASSERTION, so terms need checking before use
- README gives no setup steps for a standalone server; points to a separate demo repo
- Not AI-specific; it is a general ORM and API protocol
- no GPU
- Needs Java 1.8+, A supported database (e.g. MySQL 5.7+, PostgreSQL 9.5+)
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