Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.
Description
Renowned startpoint security software products in the IRI Data Protector suite and IRI Voracity data management platform will: classify, find, and mask personally identifiable information (PII) and other "data at risk" in almost every enterprise data source and sillo today, on-premise or in the cloud.
Each IRI data masking tool in the suite -- FieldShield, DarkShield or CellShield EE -- can help you comply (and prove compliance) with the CCPA, CIPSEA, FERPA, HIPAA/HITECH, PCI DSS, and SOC2 in the US, and international data privacy laws like the GDPR, KVKK, LGPD, LOPD, PDPA, PIPEDA and POPI.
Co-located and compatible IRI tooling in Voracity, including IRI RowGen, can also synthesize test data from scratch, and produce referentially correct (and optionally masked) database subsets.
IRI and its authorized partners around the world can help you implement fit-for-purpose compliance and breach mitigation solutions using these technologies if you need help.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon S3
No
Apache Hive
No
Astera Dataprep
Yes
Ficstar
Yes
Flyte
Yes
Hadoop
Yes
IBM Db2 Event Store
Yes
IBM Informix
No
Indexima Data Hub
Yes
Mage Sensitive Data Discovery
Yes
Integrations
Amazon S3
Yes
Apache Hive
Yes
Astera Dataprep
No
Ficstar
No
Flyte
No
Hadoop
No
IBM Db2 Event Store
No
IBM Informix
Yes
Indexima Data Hub
No
Mage Sensitive Data Discovery
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
parquet.apache.org
Vendor Details
Company Name
IRI, The CoSort Company
Founded
1978
Country
United States
Website
www.iri.com/products/iri-data-protector
Product Features
Product Features
Data Security
Alerts / Notifications
Yes
Antivirus/Malware Detection
No
At-Risk Analysis
Yes
Audits
Yes
Data Center Security
No
Data Classification
Yes
Data Discovery
Yes
Data Loss Prevention
Yes
Data Masking
Yes
Data-Centric Security
Yes
Database Security
Yes
Encryption
Yes
Identity / Access Management
Yes
Logging / Reporting
Yes
Mobile Data Security
No
Monitor Abnormalities
No
Policy Management
No
Secure Data Transport
No
Sensitive Data Compliance
Yes