Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Data serves as the fundamental asset for all digital transformation efforts. Numerous initiatives encounter obstacles due to the misconception that data quality and availability are guaranteed. Yet, the stark truth is that obtaining relevant data often proves to be challenging, costly, and disruptive. The Datumize Data Collector (DDC) functions as a versatile and lightweight middleware designed to extract data from intricate, frequently transient, and legacy data sources. This type of data often remains largely untapped since accessible methods for retrieval are lacking. By enabling organizations to gather data from various sources, DDC also facilitates extensive edge computing capabilities, which can incorporate third-party applications, such as AI models, while seamlessly integrating the output into preferred formats and storage solutions. Ultimately, DDC presents a practical approach for businesses looking to streamline their digital transformation efforts by efficiently collecting essential operational and business data. Its ability to bridge the gap between complex data environments and actionable insights makes it an invaluable tool in today's data-driven landscape.
Description
Centralize, transform, and store your data seamlessly. Logstash serves as a free and open-source data processing pipeline on the server side, capable of ingesting data from numerous sources, transforming it, and then directing it to your preferred storage solution. It efficiently handles the ingestion, transformation, and delivery of data, accommodating various formats and levels of complexity. Utilize grok to extract structure from unstructured data, interpret geographic coordinates from IP addresses, and manage sensitive information by anonymizing or excluding specific fields to simplify processing. Data is frequently dispersed across multiple systems and formats, creating silos that can hinder analysis. Logstash accommodates a wide range of inputs, enabling the simultaneous collection of events from diverse and common sources. Effortlessly collect data from logs, metrics, web applications, data repositories, and a variety of AWS services, all in a continuous streaming manner. With its robust capabilities, Logstash empowers organizations to unify their data landscape effectively.
API Access
Has API
No
API Access
Has API
No
Integrations
AiOpsX
No
Amazon CloudWatch
No
Amazon Kinesis
No
Amazon Web Services (AWS)
No
Axonius
No
Beats
No
Dash0
No
Deep.BI
No
ELLIO
No
Elastic Observability
No
Integrations
AiOpsX
Yes
Amazon CloudWatch
Yes
Amazon Kinesis
Yes
Amazon Web Services (AWS)
Yes
Axonius
Yes
Beats
Yes
Dash0
Yes
Deep.BI
Yes
ELLIO
Yes
Elastic Observability
Yes
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
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
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
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Datumize
Founded
2014
Country
Spain
Website
www.datumize.com
Vendor Details
Company Name
Elasticsearch
Founded
2012
Country
United States
Website
www.elastic.co/logstash
Product Features
Data Discovery
Contextual Search
No
Data Classification
Yes
Data Matching
Yes
False Positives Reduction
No
Self Service Data Preparation
No
Sensitive Data Identification
Yes
Visual Analytics
No
Data Extraction
Disparate Data Collection
Yes
Document Extraction
Yes
Email Address Extraction
Yes
IP Address Extraction
Yes
Image Extraction
Yes
Phone Number Extraction
Yes
Pricing Extraction
Yes
Web Data Extraction
Yes
ETL
Data Analysis
No
Data Filtering
Yes
Data Quality Control
Yes
Job Scheduling
Yes
Match & Merge
Yes
Metadata Management
No
Non-Relational Transformations
Yes
Version Control
No
Product Features
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No