SurrealDB vs Google Cloud (GCP)
A detailed comparison to help you choose between SurrealDB and Google Cloud (GCP).
Quick Verdict
3.6/5
SurrealDB
0 reviews
3.9/5
Google Cloud (GCP)
0 reviews
Google Cloud (GCP) is rated higher (3.9 vs 3.6). SurrealDB is a multi-model database that handles relational, document, graph, and full-text queries in a single database. Schema-optional, built-in auth, and real-time subscriptions. Known for its data analytics and AI tooling (BigQuery, Vertex AI).
SurrealDB Multi-model database with built-in real-time sync and WebSocket support | Google Cloud (GCP) Google's cloud — AI/ML and data analytics focus | |
|---|---|---|
| Overview | ||
| Rating | 3.6 (0 reviews) | 3.9 (0 reviews)✓ |
| Pricing model | freemium | pay-as-you-go |
| Starting price | Free tier available | Free tier available |
| Best for | Teams building real-time, multi-model applications that would otherwise combine a document database, a search engine and a graph store | Data- and ML-centric teams already building on BigQuery, GKE, or Vertex AI, and workloads that need a published multi-zone SLA or data residency in one of 43 regions. |
| Specifications (entry plan) | ||
| CPU cores | 0 vCPU | — |
| RAM | 1 GB | — |
| Storage | 1 GB | — |
| Bandwidth | — | — |
| SLA uptime | — | 99.9% |
| Data-center count | 3 | 43✓ |
| €/GB RAM/mo | €0.00 | — |
| Features | ||
| IPv6 | ✓ | |
| DDoS protection | ||
| Automated backups | ✓ | |
| Snapshots | ||
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ||
| Free tier | ||
| Data-center locations | ||
| Regions | AWS Ireland (aws-euw1), AWS US East N. Virginia (aws-use1), AWS US West Oregon (aws-usw2) | — |
| Tags | ||
| Tags | free tieropen sourceself hostableapi access | free tierhourly billingipv6gpu availables3 compatibleeu datacenterus datacenterapac datacenterapi accessterraform providerkubernetes supportarm processors |
| Visit SurrealDB → | Visit Google Cloud (GCP) → | |
SurrealDB
Pros
- + One engine for relational, document, graph, time-series and geospatial data, plus full-text and vector search
- + Transparent published rate table with a real free instance (0.25 vCPU, 1 GB memory, 1 GB storage)
- + Hourly billing keeps development and prototype instances cheap
- + Granular permissions at table, document and field level defined in the schema
- + Self-hostable under BSL 1.1 with open-source (Apache 2.0 / MIT) SDKs as an exit path
Cons
- - Young database: 1.0 in 2023 and the storage engine is still being replaced
- - Only three AWS regions (Ireland, N. Virginia, Oregon) — nothing in APAC
- - Smaller ecosystem, tooling and hiring pool than PostgreSQL or MongoDB
- - Scale plan requires a three-node minimum; several advertised features are still marked coming soon
- - Custom SLAs only at Enterprise tier; backup retention policy for free instances is ambiguous in the docs
Google Cloud (GCP)
Pros
- + Best published SLA set in the comparison: 99.99% multi-zone, 99.9% single-instance
- + 43 regions and 130 zones with per-region price variance you can trade against latency
- + Per-second billing and three discount levers — Spot up to 91% off, commitments up to 55–70%
- + Live migration through host maintenance; deep integration with GKE, BigQuery, Vertex AI
- + Real free entry: $300 trial credit that never auto-charges, plus an Always Free e2-micro VM
Cons
- - Poor price-performance for plain VMs versus European VPS specialists; no bundled transfer
- - Egress is expensive ($0.12/GiB Premium) and billed as a separate line item
- - Sustained use discounts don't apply to E2 and N4 — the families entry buyers choose
- - Budgets alert but don't cap Compute Engine spend; human support costs from $29/month
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