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What is Kylo?

Kylo is an open-source solution tailored for the proficient management of enterprise-scale data lakes, enabling users to effortlessly ingest and prepare data while integrating strong metadata management, governance, security, and best practices informed by Think Big's vast experience from over 150 large-scale data implementations. It empowers users to handle self-service data ingestion, enhanced by functionalities for data cleansing, validation, and automatic profiling. The platform features a user-friendly visual SQL and an interactive transformation interface that simplifies data manipulation. Users can investigate and navigate both data and metadata, trace data lineage, and access profiling statistics without difficulty. Moreover, it includes tools for monitoring the vitality of data feeds and services within the data lake, which aids users in tracking service level agreements (SLAs) and resolving performance challenges efficiently. Users are also capable of creating and registering batch or streaming pipeline templates through Apache NiFi, which further supports self-service capabilities. While organizations often allocate significant engineering resources to migrate data into Hadoop, they frequently grapple with governance and data quality issues; however, Kylo streamlines the data ingestion process, allowing data owners to exert control through its intuitive guided user interface. This revolutionary approach not only boosts operational effectiveness but also cultivates a sense of data ownership among users, thereby transforming the organizational culture towards data management. Ultimately, Kylo represents a significant advancement in making data management more accessible and efficient for all stakeholders involved.

What is Azure Data Lake?

Azure Data Lake offers a comprehensive set of features that empower developers, data scientists, and analysts to easily store all kinds of data, regardless of their size or format, while also enabling various processing and analytical tasks across multiple platforms and programming languages. By resolving the complexities related to data ingestion and storage, it greatly speeds up the process of initiating batch, streaming, and interactive analytics. Furthermore, Azure Data Lake is engineered to seamlessly integrate with existing IT infrastructures concerning identity, management, and security, thereby streamlining data governance and overall management. It also allows for smooth integration with operational databases and data warehouses, which helps users enhance their existing data applications. Drawing on a wealth of experience with enterprise clients and handling significant data processing and analytics workloads for major Microsoft services including Office 365, Xbox Live, Azure, Windows, Bing, and Skype, Azure Data Lake effectively tackles numerous productivity and scalability challenges that can impede optimal data use. As a result, organizations can effectively harness this robust platform to fully unlock the potential of their data assets, fostering improved decision-making processes and innovative insights that drive business growth. This makes Azure Data Lake not just a tool, but a strategic asset for organizations looking to transform their data into actionable intelligence.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Elasticsearch
HashiCorp Vault
OpenText Data Privacy & Protection Foundation
Talend Data Preparation

Integrations Supported

Alpine IQ
Apache Hudi
Azure Data Factory
Azure Data Lake Storage
Clarity by Rego
Dasera
Hyper Historian
Microsoft Power BI
Openbridge
Privacera
Streamkap
Validio

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Teradata

Date Founded

1979

Company Location

United States

Company Website

kylo.io

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/solutions/data-lake/

Categories and Features

Data Governance

Not specified

Data Lake

Not specified

Data Lineage

Not specified

Data Preparation

Not specified

Metadata Management

Not specified

Categories and Features

Data Lake

Not specified

Object Storage

Not specified

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