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What is OpenObserve?

OpenObserve is a powerful open-source observability platform tailored for the management of logs, metrics, and traces, with a strong emphasis on high performance, scalability, and significantly lower costs. It facilitates observability at an immense scale, capable of handling petabytes of data through features like columnar storage data compression and the option to "bring your own bucket" for storage, whether on local disks or cloud services such as S3, GCS, and Azure Blob. Engineered in Rust, OpenObserve employs the DataFusion query engine for direct querying of Parquet files, offering a stateless, horizontally scalable architecture that implements caching strategies for both results and disk, ensuring swift performance even under peak traffic conditions. By following open standards and maintaining compatibility with OpenTelemetry and vendor-neutral APIs, OpenObserve integrates effortlessly into existing monitoring and logging frameworks. Its core features include logs, metrics, traces, frontend monitoring, pipelines, alerts, and detailed dashboards for effective visualizations. This comprehensive platform not only enhances observability but also streamlines data management processes for organizations aiming for operational efficiency. By adopting OpenObserve, businesses can realize significant improvements in their observability practices while managing costs effectively.

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 Web Services (AWS)

Integrations Supported

3LC
APERIO DataWise
Amazon Data Firehose
Blotout
Gable
Gravity Data
GribStream
IBM Db2 Event Store
Indexima Data Hub
OpenObserve
QStudio
Querri
QuerySurge
SSIS Integration Toolkit
StarfishETL
Tad
Visplore
Warp 10

API Availability

Has API

API Availability

Pricing Information

$0.30 per GB
Free Version

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
Webinars
Online Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

OpenObserve

Date Founded

2022

Company Location

United States

Company Website

openobserve.ai/

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

Observability

Not specified

Categories and Features

Columnar Databases

Not specified

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