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ease
features
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support

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Description

Numerous customers of Amazon Web Services (AWS) seek a data storage and analytics solution that surpasses the agility and flexibility of conventional data management systems. A data lake has emerged as an innovative and increasingly favored method for storing and analyzing data, as it enables organizations to handle various data types from diverse sources, all within a unified repository that accommodates both structured and unstructured data. The AWS Cloud supplies essential components necessary for customers to create a secure, adaptable, and economical data lake. These components comprise AWS managed services designed to assist in the ingestion, storage, discovery, processing, and analysis of both structured and unstructured data. To aid our customers in constructing their data lakes, AWS provides a comprehensive data lake solution, which serves as an automated reference implementation that establishes a highly available and cost-efficient data lake architecture on the AWS Cloud, complete with an intuitive console for searching and requesting datasets. Furthermore, this solution not only enhances data accessibility but also streamlines the overall data management process for organizations.

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. For further information, you can download it here: https://sourceforge.net/projects/logstash.mirror/

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Activeeon ProActive
Amazon CloudWatch
Amazon Kinesis
Amazon OpenSearch Service
Amazon Redshift
Amazon Simple Queue Service (SQS)
Amazon Web Services (AWS)
Axonius
Coralogix
Deep.BI
KrakenD
OctoData
RabbitMQ
Redis
SQLite
Squadcast
Stamus Networks
StrongDM
X (Twitter)
groundcover

Integrations

Activeeon ProActive
Amazon CloudWatch
Amazon Kinesis
Amazon OpenSearch Service
Amazon Redshift
Amazon Simple Queue Service (SQS)
Amazon Web Services (AWS)
Axonius
Coralogix
Deep.BI
KrakenD
OctoData
RabbitMQ
Redis
SQLite
Squadcast
Stamus Networks
StrongDM
X (Twitter)
groundcover

Pricing Details

No price information available.
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

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/solutions/implementations/data-lake-solution/

Vendor Details

Company Name

Elasticsearch

Founded

2012

Country

United States

Website

www.elastic.co/logstash

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Product Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Alternatives

Alternatives

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