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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Azure Data Lake offers a comprehensive set of features designed to facilitate the storage of data in any form, size, and speed for developers, data scientists, and analysts alike, enabling a wide range of processing and analytics across various platforms and programming languages. By simplifying the ingestion and storage of data, it accelerates the process of launching batch, streaming, and interactive analytics. Additionally, Azure Data Lake is compatible with existing IT frameworks for identity, management, and security, which streamlines data management and governance. Its seamless integration with operational stores and data warehouses allows for the extension of current data applications without disruption. Leveraging insights gained from working with enterprise clients and managing some of the world's largest processing and analytics tasks for services such as Office 365, Xbox Live, Azure, Windows, Bing, and Skype, Azure Data Lake addresses many of the scalability and productivity hurdles that hinder your ability to fully utilize data. Ultimately, it empowers organizations to harness their data's potential more effectively and efficiently than ever before.

Description

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Alpine IQ
Azure Data Factory
Azure Data Lake Analytics
Azure Data Lake Storage
Azure Databricks
Clarity by Rego
Electrik.Ai
Google Cloud Lakehouse
Hive
Hyper Historian
JSCAPE MFT Server
Micromerce
Microsoft Azure
Microsoft Power BI
Privacera
PubSub+ Platform
PuppyGraph
QuerySurge
StarfishETL
Visual Studio

Integrations

Alpine IQ
Azure Data Factory
Azure Data Lake Analytics
Azure Data Lake Storage
Azure Databricks
Clarity by Rego
Electrik.Ai
Google Cloud Lakehouse
Hive
Hyper Historian
JSCAPE MFT Server
Micromerce
Microsoft Azure
Microsoft Power BI
Privacera
PubSub+ Platform
PuppyGraph
QuerySurge
StarfishETL
Visual Studio

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

Microsoft

Founded

1975

Country

United States

Website

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

Vendor Details

Company Name

Upsolver

Founded

2014

Country

Israel

Website

www.upsolver.com

Product Features

Product Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Data Preparation

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

Alternatives

Alternatives

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