High-Volume Data Masking
Scaling Data Masking for High-Volume Workloads​
Protecto offers features such as asynchronous APIs, queuing and audit trails to avoid common hurdles in large scale data masking/de-identification. ​
- Trusted by Engineering Teams Building AI at Scale
Overcoming High-Volume Data Masking Obstacles
Masking large datasets brings challenges that go beyond adding additional infrastructure. Traditional tools like Microsoft Presidio and AWS Comprehend aren’t built for high data volumes, making large-scale masking complex and cumbersome, often resulting in slower processing, bottlenecks, and failures.​
- High Latency: Significant delays in processing large datasets
- Lack of Batch Processing: Limited support for queuing and batch-based data masking
- Scaling Difficulties: Manual intervention required to scale resources
- Accuracy Issues: Decreased PII detection accuracy at high volumes
- Cost Inefficiencies: Escalating infrastructure costs due to scaling challenges
Protecto vs. Generic Data Masking Tools
Overcome the challenges of large-scale data processing with Protecto’s advanced masking solution—optimized for accuracy, scalability, and seamless integration, while keeping infrastructure costs low.
| Features | Protecto | Others |
|---|---|---|
| PII Masking | ✓ Advanced, with context retention | ! Basic, error-prone for unstructured data |
| PII Identification Accuracy | ✓ Highly accurate | ! Moderate, requires manual fine-tuning |
| Unstructured Data Masking | ✓ Context-retaining, semantic accuracy | ! Prone to errors, loses context |
| Latency | ✓ Low, optimized for large datasets | ✕ High, especially with unstructured data |
| Scalability | ✓ Auto-scaling based on volume | ! Limited, needs manual intervention |
| Error Handling | ✓ Robust with retries | ! Basic, manual intervention needed |
| Asynchronous Processing | ✓ Built-in queuing | ! Limited, extra setup required |
| Cost Efficiency | ✓ Optimized for GPU/CPU cost-efficiency | ✕ Higher costs due to scaling inefficiencies |
| High-Volume Performance | ✓ High throughput, low latency | ! Struggles at scale |
| ETL Tool Integration | ✓ Seamless with Spark, Kafka, etc. | ! Limited ETL integration |
| Infrastructure Costs | ✓ Auto-scales to reduce costs | ✕ High due to manual scaling |
Scalable Large-Scale Data Masking​
Protecto delivers scalable, accurate data masking tailored for large enterprise data volumes.​
Accurate PII Masking
- Achieve higher accuracy in identifying and masking sensitive data
- Maintain context-preserving masking for unstructured text
Scalable Processing
- Implement dynamic auto-scaling to handle fluctuating data volumes
- Leverage asynchronous processing with built-in queuing system
Exceptional Performance
- Achieve low-latency masking even at high throughputs
- Seamlessly integrated with any existing data pipelines
How a Leading SaaS Company Masked 13M Daily Texts to Power Their AI Innovation
In just one week, Protecto helped the SaaS company cut costs by 90%, achieve 100% compliance, and launch AI features ahead of competitors. The solution streamlined operations with 10X efficiency, reinforcing their reputation as a privacy-first leader.
Built for Enterprise. Optimized for Scale.
On-Premises or SaaS
Deploy Protecto on your servers or consume it as SaaS. Either way, get the full benefits including multitenancy.
Simple APIs
Use sync and async APIs to integrate with any part: preprocessing, context data, prompt, or response.
Auto-scale
Protecto's architecture scales to process billions of rows or runs lightweight on-edge devices, offering versatility and efficiency.