Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Numerous customers of Amazon Web Services (AWS) seek a data storage and analytics solution that surpasses the agility and flexibility of conventional data management systems. A data lake has emerged as an innovative and increasingly favored method for storing and analyzing data, as it enables organizations to handle various data types from diverse sources, all within a unified repository that accommodates both structured and unstructured data. The AWS Cloud supplies essential components necessary for customers to create a secure, adaptable, and economical data lake. These components comprise AWS managed services designed to assist in the ingestion, storage, discovery, processing, and analysis of both structured and unstructured data. To aid our customers in constructing their data lakes, AWS provides a comprehensive data lake solution, which serves as an automated reference implementation that establishes a highly available and cost-efficient data lake architecture on the AWS Cloud, complete with an intuitive console for searching and requesting datasets. Furthermore, this solution not only enhances data accessibility but also streamlines the overall data management process for organizations.
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
Eco
No
Hive
No
Micromerce
No
PuppyGraph
No
Rocket Data Replicate & Sync
Yes
VE3 DataWise
Yes
Integrations
AWS IoT SiteWise
Yes
Eco
Yes
Hive
Yes
Micromerce
Yes
PuppyGraph
Yes
Rocket Data Replicate & Sync
No
VE3 DataWise
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
No
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
No
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
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/solutions/implementations/data-lake-solution/
Vendor Details
Company Name
Upsolver
Founded
2014
Country
Israel
Website
www.upsolver.com
Product Features
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
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