Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Introducing a unique cloud data lakehouse that is entirely managed and capable of ingesting data from all your sources within minutes, while seamlessly accommodating every query engine at scale, all at a significantly reduced cost. This platform enables ingestion from both databases and event streams at terabyte scale in near real-time, offering the ease of fully managed pipelines. Furthermore, you can execute queries using any engine, catering to diverse needs such as business intelligence, real-time analytics, and AI/ML applications. By adopting this solution, you can reduce your expenses by over 50% compared to traditional cloud data warehouses and ETL tools, thanks to straightforward usage-based pricing. Deployment is swift, taking just minutes, without the burden of engineering overhead, thanks to a fully managed and highly optimized cloud service. Consolidate your data into a single source of truth, eliminating the necessity of duplicating data across various warehouses and lakes. Select the appropriate table format for each task, benefitting from seamless interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Additionally, quickly set up managed pipelines for change data capture (CDC) and streaming ingestion, ensuring that your data architecture is both agile and efficient. This innovative approach not only streamlines your data processes but also enhances decision-making capabilities across your organization.
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
PuppyGraph
Yes
Alibaba Cloud
Yes
Amazon MSK
Yes
Amazon S3
Yes
Apache Cassandra
Yes
Apache Iceberg
Yes
BytePlus Translate
Yes
Databricks
Yes
Eco
No
Google Cloud BigQuery
Yes
Integrations
PuppyGraph
Yes
Alibaba Cloud
No
Amazon MSK
No
Amazon S3
No
Apache Cassandra
No
Apache Iceberg
No
BytePlus Translate
No
Databricks
No
Eco
Yes
Google Cloud BigQuery
No
Pricing Details
No price information available.
Free Trial
Yes
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)
Yes
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)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Onehouse
Country
United States
Website
www.onehouse.ai/
Vendor Details
Company Name
Upsolver
Founded
2014
Country
Israel
Website
www.upsolver.com
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
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