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Description
Apache DataFusion is a versatile and efficient query engine crafted in Rust, leveraging Apache Arrow for its in-memory data representation. It caters to developers engaged in creating data-focused systems, including databases, data frames, machine learning models, and real-time streaming applications. With its SQL and DataFrame APIs, DataFusion features a vectorized, multi-threaded execution engine that processes data streams efficiently and supports various partitioned data sources. It is compatible with several native formats such as CSV, Parquet, JSON, and Avro, and facilitates smooth integration with popular object storage solutions like AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture includes a robust query planner and an advanced optimizer that boasts capabilities such as expression coercion, simplification, and optimizations that consider distribution and sorting, along with automatic reordering of joins. Furthermore, DataFusion allows for extensive customization, enabling developers to incorporate user-defined scalar, aggregate, and window functions along with custom data sources and query languages, making it a powerful tool for diverse data processing needs. This adaptability ensures that developers can tailor the engine to fit their unique use cases effectively.
Description
Tenzir is a specialized data pipeline engine tailored for security teams, streamlining the processes of collecting, transforming, enriching, and routing security data throughout its entire lifecycle. It allows users to efficiently aggregate information from multiple sources, convert unstructured data into structured formats, and adjust it as necessary. By optimizing data volume and lowering costs, Tenzir also supports alignment with standardized schemas such as OCSF, ASIM, and ECS. Additionally, it guarantees compliance through features like data anonymization and enhances data by incorporating context from threats, assets, and vulnerabilities. With capabilities for real-time detection, it stores data in an efficient Parquet format within object storage systems. Users are empowered to quickly search for and retrieve essential data, as well as to reactivate dormant data into operational status. The design of Tenzir emphasizes flexibility, enabling deployment as code and seamless integration into pre-existing workflows, ultimately seeking to cut SIEM expenses while providing comprehensive control over data management. This approach not only enhances the effectiveness of security operations but also fosters a more streamlined workflow for teams dealing with complex security data.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
Apache Parquet
Azure Blob Storage
Google Cloud Storage
Python
Amazon MSK
Amazon Security Lake
Amazon Simple Queue Service (SQS)
Apache Arrow
ClickHouse
Integrations
Amazon S3
Apache Parquet
Azure Blob Storage
Google Cloud Storage
Python
Amazon MSK
Amazon Security Lake
Amazon Simple Queue Service (SQS)
Apache Arrow
ClickHouse
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Apache Software Foundation
Founded
2019
Country
United States
Website
datafusion.apache.org
Vendor Details
Company Name
Tenzir
Founded
2017
Country
Germany
Website
tenzir.com
Product Features
Database
Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization