Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Grafana Cloud Reviews & Ratings
    4.5 out of 5 stars 861 Ratings
    Company Website for Grafana Cloud
  • NeuBird Reviews & Ratings
    5.0 out of 5 stars 2 Ratings
    Company Website for NeuBird
  • New Relic Reviews & Ratings
    4.5 out of 5 stars 2,941 Ratings
    Company Website for New Relic
  • Graylog Reviews & Ratings
    4.5 out of 5 stars 440 Ratings
    Company Website for Graylog
  • DataBuck Reviews & Ratings
    4.8 out of 5 stars 6 Ratings
    Company Website for DataBuck
  • AdRem NetCrunch Reviews & Ratings
    4.6 out of 5 stars 165 Ratings
    Company Website for AdRem NetCrunch
  • Auvik Reviews & Ratings
    4.5 out of 5 stars 678 Ratings
    Company Website for Auvik
  • ManageEngine EventLog Analyzer Reviews & Ratings
    4.3 out of 5 stars 211 Ratings
    Company Website for ManageEngine EventLog Analyzer
  • Safetica Reviews & Ratings
    4.7 out of 5 stars 416 Ratings
    Company Website for Safetica
  • ManageEngine Log360 Reviews & Ratings
    4.5 out of 5 stars 196 Ratings
    Company Website for ManageEngine Log360

What is Tenzir?

Tenzir serves as a dedicated data pipeline engine designed specifically for security teams, simplifying the collection, transformation, enrichment, and routing of security data throughout its lifecycle. Users can effortlessly gather data from various sources, convert unstructured information into organized structures, and modify it as needed. Tenzir optimizes data volume and minimizes costs, while also ensuring compliance with established schemas such as OCSF, ASIM, and ECS. Moreover, it incorporates features like data anonymization to maintain compliance and enriches data by adding context related to threats, assets, and vulnerabilities. With its real-time detection capabilities, Tenzir efficiently stores data in a Parquet format within object storage systems, allowing users to quickly search for and access critical data as well as revive inactive data for operational use. The design prioritizes flexibility, facilitating deployment as code and smooth integration into existing workflows, with the goal of reducing SIEM costs while granting extensive control over data management. This innovative approach not only boosts the efficiency of security operations but also streamlines workflows for teams navigating the complexities of security data, ultimately contributing to a more secure digital environment. Furthermore, Tenzir's adaptability helps organizations stay ahead of emerging threats in an ever-evolving landscape.

What is Apache Parquet?

Parquet was created to offer the advantages of efficient and compressed columnar data formats across all initiatives within the Hadoop ecosystem. It takes into account complex nested data structures and utilizes the record shredding and assembly method described in the Dremel paper, which we consider to be a superior approach compared to just flattening nested namespaces. This format is specifically designed for maximum compression and encoding efficiency, with numerous projects demonstrating the substantial performance gains that can result from the effective use of these strategies. Parquet allows users to specify compression methods at the individual column level and is built to accommodate new encoding technologies as they arise and become accessible. Additionally, Parquet is crafted for widespread applicability, welcoming a broad spectrum of data processing frameworks within the Hadoop ecosystem without showing bias toward any particular one. By fostering interoperability and versatility, Parquet seeks to enable all users to fully harness its capabilities, enhancing their data processing tasks in various contexts. Ultimately, this commitment to inclusivity ensures that Parquet remains a valuable asset for a multitude of data-centric applications.

Media

Media

Integrations Supported

Amazon S3
Amazon Security Lake
Azure Blob Storage
Python
Snowflake
Splunk Cloud Platform
Zeek
Zscaler

Integrations Supported

3LC
Amazon Data Firehose
Flyte
Mage Platform
OrcaSheets
PI.EXCHANGE
Querri
QuerySurge
Streamkap
Timbr.ai
Warp 10
e6data

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Tenzir

Date Founded

2017

Company Location

Germany

Company Website

tenzir.com

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

Cloud Security

Not specified

Data Anonymization

Not specified

Data Pipeline

Not specified

Data Security

Not specified

Log Management

Not specified

Observability

Not specified

Telemetry

Not specified

Categories and Features

Columnar Databases

Not specified

Popular Alternatives

Popular Alternatives

Apache Iceberg Reviews & Ratings

Apache Iceberg

Apache Software Foundation
Datadog Reviews & Ratings

Datadog

4.9 out of 5 stars