Comparison
Blindfold vs Google Cloud DLP
Both detect and protect PII, but Blindfold offers a simpler API, built-in compliance policies, and works outside the Google Cloud ecosystem.
At a glance
| Feature | Blindfold | Google Cloud DLP |
|---|---|---|
| Type | Managed API | GCP service |
| Cloud lock-in | None — works anywhere | Google Cloud only |
| PII methods | 7 (tokenize, redact, mask, hash, synthesize, encrypt, detect) | Inspect + de-identify (redact, mask, crypto, bucketing) |
| Reversible tokenization | Yes — tokenize + detokenize | Crypto-based (requires KMS) |
| Compliance policies | GDPR, HIPAA, PCI DSS, strict | None built-in |
| Data residency | EU (Frankfurt) / US (Virginia) | GCP region dependent |
| InfoTypes | Auto-detected per policy | 200+ (manual configuration) |
| Setup complexity | API key — 2 minutes | GCP project + service account + IAM + API enable |
| Languages | 18+ | Varies by infoType |
| Pricing | Free tier + usage-based | Per GB inspected/transformed |
Key differences
Simple API vs complex GCP setup
Blindfold requires an API key — that's it. Google Cloud DLP requires a GCP project, enabling the DLP API, creating a service account, configuring IAM permissions, and learning the DLP-specific request format. The learning curve is significant.
Reversible tokenization built-in
Blindfold's tokenize/detokenize is a core feature that works out of the box. Google Cloud DLP offers cryptographic de-identification via Cloud KMS, but it requires setting up KMS keys, configuring crypto transforms, and managing the key lifecycle yourself.
No cloud lock-in
Blindfold works with any cloud provider, framework, or language. Google Cloud DLP is a GCP-only service — if you use it, your PII detection pipeline is tied to Google Cloud infrastructure.
Compliance policies vs manual configuration
Blindfold has pre-configured compliance policies (GDPR, HIPAA, PCI DSS) that select the right infoTypes and thresholds automatically. With Cloud DLP, you manually specify which of the 200+ infoTypes to scan for and configure custom likelihood thresholds.
When to choose each
Choose Blindfold when
- You need reversible tokenization without managing KMS keys
- You want to avoid Google Cloud lock-in
- You prefer a simple API over complex GCP configuration
- You need built-in compliance policies
- You want a free tier to get started
Choose Google Cloud DLP when
- You're already deeply invested in Google Cloud
- You need to scan BigQuery, Cloud Storage, or Datastore natively
- You need very specific infoType detectors from the 200+ catalog
- You want to use DLP with other GCP data tools (Dataflow, etc.)
Code comparison
from blindfold import Blindfold client = Blindfold() # Detect PII with GDPR policy result = client.detect( text, policy="gdpr_eu" ) # Tokenize — reversible safe = client.tokenize(text)
import google.cloud.dlp_v2 client = google.cloud.dlp_v2.DlpServiceClient() inspect_config = { "info_types": [ {"name": "PERSON_NAME"}, {"name": "EMAIL_ADDRESS"}, {"name": "PHONE_NUMBER"}, ], "min_likelihood": "LIKELY", } resp = client.inspect_content( request={ "parent": f"projects/{project}", "inspect_config": inspect_config, "item": { "value": text }, } )
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