Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
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
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
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