TigerData vs Google Cloud (GCP)
A detailed comparison to help you choose between TigerData and Google Cloud (GCP).
Quick Verdict
4.2/5
TigerData
0 reviews
3.9/5
Google Cloud (GCP)
0 reviews
TigerData is rated higher (4.2 vs 3.9). TigerData, from the creators of TimescaleDB, is a PostgreSQL cloud platform built for time-series and real-time analytics workloads at large scale, aimed at developers and enterprises. Known for its data analytics and AI tooling (BigQuery, Vertex AI).
TigerData PostgreSQL-native time-series database for metrics, events, and analytics | Google Cloud (GCP) Google's cloud — AI/ML and data analytics focus | |
|---|---|---|
| Overview | ||
| Rating | 4.2 (0 reviews)✓ | 3.9 (0 reviews) |
| Pricing model | freemium | pay-as-you-go |
| Starting price | From $30/mo | Free tier available✓ |
| Best for | Teams building observability, IoT/telemetry, financial or real-time analytics platforms who want time-series performance inside standard PostgreSQL and can run the ops model of a managed Postgres service. | 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. |
| Features | ||
| IPv6 | ✓ | |
| DDoS protection | ||
| Automated backups | ✓ | |
| Snapshots | ✓ | |
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ||
| Free tier | ✓ | |
| Data-center locations | ||
| Regions | 13 AWS regions + 4 Azure regions across North America, Europe, Asia Pacific and South America | — |
| Tags | ||
| Tags | free tiermanaged optionbackups includedeu datacenterus datacenterapi accessopen source | free tierhourly billingipv6gpu availables3 compatibleeu datacenterus datacenterapac datacenterapi accessterraform providerkubernetes supportarm processors |
| Visit TigerData → | Visit Google Cloud (GCP) → | |
TigerData
Pros
- + Full SQL and the PostgreSQL extension ecosystem — hypertables, continuous aggregates and 90%+ compression without a new query language
- + Published consumption pricing (compute from $30/month, storage $0.177-0.212/GB-month) with hourly metering and no instance-size lock-in
- + 17 regions across AWS and Azure with EU, US and APAC residency selectable at creation
- + Reliability productized: multi-AZ HA, PITR up to 14 days, backup retention to 180 days, cross-region restore, public SLA and status page
- + Open-source TimescaleDB escape hatch — self-hosting stays viable, which keeps pricing honest
Cons
- - Hourly compute meter bills full hours and forgotten scale-ups at the higher config are expensive
- - Serious reliability and security features (multi-node HA, 14-day PITR, SOC 2, private endpoints) gated behind Scale or Enterprise
- - PostgreSQL and time-series concepts (chunks, compression/retention policies) assumed — not a zero-ops database for non-database teams
- - Effective storage price assumes 5x compression; actual ratios are workload-dependent
- - Aiven-partnered legacy MST product carries a different (99.99%) SLA — easy to confuse with Tiger Cloud
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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