github.com/dgraph-io/dgraph

The dgraph-io/dgraph package is actually the full database server, not just a client library. This creates confusion since most Go packages are clients. The actual client (dgo) is separate. Running Dgraph in production requires careful attention to resource management - it's memory-hungry and you'll need to tune badger settings aggressively to avoid OOM kills under load.

Connection pooling with dgo clients requires manual management through gRPC connection pools. There's no automatic retry logic, so you'll implement your own backoff strategies. The observability story is mixed - logs are verbose but structured logging isn't consistent across versions. Timeout configuration exists but defaults are surprisingly aggressive for distributed queries.

The biggest operational pain point is version compatibility. Schema migrations between versions can be breaking, and the 1.2.8 release from 2020 is ancient by Go standards. Backup/restore operations block other operations, and graceful shutdowns under load require careful orchestration. The alpha/raft protocol adds complexity when debugging connection issues in clustered deployments.

Running Dgraph in production requires substantial operational investment. The cluster management is complex, especially around rebalancing and zero node coordination. Connection pooling with the dgo client works reasonably well, but you'll need to implement your own circuit breakers and sophisticated retry logic as the built-in error handling is minimal. Transaction conflicts under concurrent load require careful application-level handling.

Memory usage can spike unpredictably during large queries or bulk mutations, making capacity planning challenging. The timeout configuration exists but default values are often too generous for production workloads. Observability is limited - you'll need to instrument heavily around the client calls since the library provides minimal structured logging hooks. Breaking changes between minor versions have been problematic, particularly around schema migration paths.

The version referenced (1.2.8 from 2020) is significantly outdated and shouldn't be used for new projects. Current maintained versions have improved some issues but the fundamental operational complexity remains. The performance can be excellent for graph traversals when properly tuned, but getting there requires deep expertise.

The Dgraph Go client requires significant upfront investment to understand its query language (GraphQL+- and DQL) and mutation patterns. The API design feels closer to raw database interaction than an idiomatic Go library. You'll spend time converting between proto messages, JSON, and Go structs. Type safety is minimal - queries are strings, and unmarshaling results requires manual struct tags and careful error handling.

Documentation exists but assumes familiarity with graph concepts and Dgraph's specific semantics. Error messages often reference internal implementation details rather than user-facing problems. The transaction API works but lacks the ergonomics of modern ORMs - you manually manage commits, rollbacks, and retries. IDE autocompletion helps little since most interactions are string-based queries.

The package hasn't been updated since 2020, which shows in its pre-generics design and lack of modern Go patterns. Migration between Dgraph versions can be painful as schema changes require careful coordination. For simple use cases, you'll write more boilerplate than expected; for complex graph queries, the power is there but buried under API friction.