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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Utilize Azure Table storage to manage petabytes of semi-structured data efficiently while keeping expenses low. In contrast to various data storage solutions, whether local or cloud-based, Table storage enables seamless scaling without the need for manual sharding of your dataset. Additionally, concerns about data availability are mitigated through the use of geo-redundant storage, which ensures that data is replicated three times within a single region and an extra three times in a distant region, enhancing data resilience. This storage option is particularly advantageous for accommodating flexible datasets—such as user data from web applications, address books, device details, and various other types of metadata—allowing you to develop cloud applications without restricting the data model to specific schemas. Each row in a single table can possess a unique structure, for instance, featuring order details in one entry and customer data in another, which grants you the flexibility to adapt your application and modify the table schema without requiring downtime. Furthermore, Table storage is designed with a robust consistency model to ensure reliable data access. Overall, it provides an adaptable and scalable solution for modern data management needs.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS IoT SiteWise No 
Auth.js Yes 
Autymate Yes 
DQ Studio Yes 
Data Sentinel Yes 
Eco No 
Hive No 
Micromerce No 
Microsoft Azure Yes 
NXLog Yes 
PuppyGraph No 
SSIS Integration Toolkit Yes 
StarfishETL Yes 

Integrations

AWS IoT SiteWise Yes 
Auth.js No 
Autymate No 
DQ Studio No 
Data Sentinel No 
Eco Yes 
Hive Yes 
Micromerce Yes 
Microsoft Azure No 
NXLog No 
PuppyGraph Yes 
SSIS Integration Toolkit No 
StarfishETL No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/services/storage/tables/#features

Vendor Details

Company Name

Upsolver

Founded

2014

Country

Israel

Website

www.upsolver.com

Product Features

NoSQL Database

Auto-sharding No 
Automatic Database Replication No 
Data Model Flexibility No 
Deployment Flexibility No 
Dynamic Schemas No 
Integrated Caching No 
Multi-Model No 
Performance Management No 
Security Management No 

Product Features

Big Data

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

Data Mining

Data Extraction No 
Data Visualization No 
Fraud Detection No 
Linked Data Management No 
Machine Learning No 
Predictive Modeling No 
Semantic Search No 
Statistical Analysis No 
Text Mining No 

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

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