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What is Qlik Compose?

Qlik Compose for Data Warehouses provides a modern approach that simplifies and improves the setup and management of data warehouses. This innovative tool automates warehouse design, generates ETL code, and implements updates rapidly, all while following recognized best practices and strong design principles. By leveraging Qlik Compose for Data Warehouses, organizations can significantly reduce the time, costs, and risks associated with business intelligence projects, regardless of whether they are hosted on-premises or in the cloud. Conversely, Qlik Compose for Data Lakes facilitates the creation of datasets ready for analytics by automating the processes involved in data pipelines. By managing data ingestion, schema configuration, and continuous updates, companies can realize a faster return on investment from their data lake assets, thereby strengthening their overall data strategy. Ultimately, these powerful tools enable organizations to efficiently harness their data potential, leading to improved decision-making and business outcomes. With the right implementation, they can transform how data is utilized across various sectors.

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.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Apache Spark
BLUE Software
BiG EVAL
Elasticsearch
Hadoop
HashiCorp Vault
MySQL
OpenText Voltage SecureData
Pantomath
QVANTUM
Rayven
Talend Data Preparation
ThoughtSpot
VirtualBox
bipp

Integrations Supported

Amazon Web Services (AWS)
Apache Spark
BLUE Software
BiG EVAL
Elasticsearch
Hadoop
HashiCorp Vault
MySQL
OpenText Voltage SecureData
Pantomath
QVANTUM
Rayven
Talend Data Preparation
ThoughtSpot
VirtualBox
bipp

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Qlik

Date Founded

1993

Company Location

United States

Company Website

www.qlik.com/us/products/qlik-compose-data-warehouses

Company Facts

Organization Name

Teradata

Date Founded

1979

Company Location

United States

Company Website

kylo.io

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Categories and Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

Data Lineage

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

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