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What is Upsolver?

Upsolver simplifies the creation of a governed data lake while facilitating the management, integration, and preparation of streaming data for analytical purposes. Users can effortlessly build pipelines using SQL with auto-generated schemas on read. The platform includes a visual integrated development environment (IDE) that streamlines the pipeline construction process. It also allows for Upserts in data lake tables, enabling the combination of streaming and large-scale batch data. With automated schema evolution and the ability to reprocess previous states, users experience enhanced flexibility. Furthermore, the orchestration of pipelines is automated, eliminating the need for complex Directed Acyclic Graphs (DAGs). The solution offers fully-managed execution at scale, ensuring a strong consistency guarantee over object storage. There is minimal maintenance overhead, allowing for analytics-ready information to be readily available. Essential hygiene for data lake tables is maintained, with features such as columnar formats, partitioning, compaction, and vacuuming included. The platform supports a low cost with the capability to handle 100,000 events per second, translating to billions of events daily. Additionally, it continuously performs lock-free compaction to solve the "small file" issue. Parquet-based tables enhance the performance of quick queries, making the entire data processing experience efficient and effective. This robust functionality positions Upsolver as a leading choice for organizations looking to optimize their data management strategies.

What is Google Cloud Lakehouse?

Google Cloud Lakehouse is an advanced data platform that unifies data warehouses and data lakes into a single, integrated storage and analytics solution. It enables organizations to work with open data formats such as Apache Iceberg, Parquet, and ORC, ensuring flexibility and interoperability across systems. By allowing access to a single copy of data, it eliminates the need for duplication and complex data pipelines. The platform includes a centralized runtime catalog for managing metadata, resources, and access controls efficiently. It provides fine-grained security through IAM roles and table-level permissions, ensuring strong governance and compliance. Google Cloud Lakehouse supports scalable data processing and integrates with tools like Apache Spark for advanced analytics and machine learning workflows. It is designed to handle large volumes of data while maintaining performance and reliability. The platform includes features for replication and disaster recovery, helping ensure data availability and resilience. Comprehensive documentation, guides, and training resources make it easier for teams to get started and optimize their workflows. It also simplifies the management of Iceberg tables and other data structures. The system supports modern data architectures, enabling seamless integration with other Google Cloud services. By unifying storage and analytics, it reduces operational complexity and improves efficiency. Overall, Google Cloud Lakehouse empowers organizations to manage, analyze, and scale their data more effectively in a single platform.

Media

Media

Integrations Supported

AWS IoT SiteWise
Eco
Hive
Micromerce
PuppyGraph

Integrations Supported

Amazon S3
Apache Iceberg
Apache Spark
Azure Data Lake
Google Cloud BigQuery
Google Cloud Storage
Presto

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

$5 per TB
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

Upsolver

Date Founded

2014

Company Location

Israel

Company Website

www.upsolver.com

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

docs.cloud.google.com/lakehouse/docs

Categories and Features

Big Data

Data Blends
Data Cleansing
Data Mining
High Volume Processing
No-Code Sandbox

Data Integration

Not specified

Data Lake

Not specified

Data Mining

Not specified

Data Pipeline

Not specified

Data Preparation

Not specified

Categories and Features

Data Lake

Not specified

Data Warehouse

Not specified

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