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Description

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

Description

Google Cloud Lakehouse is a modern data storage and management solution that combines the capabilities of data warehouses and data lakes into a unified platform. It enables organizations to store, access, and analyze data in open formats like Apache Iceberg, Parquet, and ORC without duplication. By maintaining a single source of truth, the platform eliminates the need for complex data movement and reduces operational overhead. It offers fine-grained security controls, allowing organizations to manage access and governance policies effectively. The Lakehouse runtime catalog provides centralized metadata management and simplifies resource organization. The platform supports scalable analytics and integrates seamlessly with tools like Apache Spark for advanced data processing. It is designed to handle large-scale data workloads while maintaining high performance and reliability. Built-in best practices and guides help users optimize their data architecture. It also supports replication and disaster recovery for enhanced resilience. Overall, Google Cloud Lakehouse provides a flexible and efficient way to unify and analyze enterprise data.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Data Wrangler Yes 
Autymate Yes 
Azure Data Lake No 
Data Sentinel Yes 
Gable Yes 
Google Cloud Storage No 
Gravity Data Yes 
MLJAR Studio Yes 
Meltano Yes 
OpenObserve Yes 
PuppyGraph Yes 
QuerySurge Yes 
SDF Yes 
Semarchy xDI Yes 
Streamkap Yes 
Tenzir Yes 
Tictable Yes 
Timbr.ai Yes 
Tonic Ephemeral Yes 
Warp 10 Yes 

Integrations

Amazon SageMaker Data Wrangler No 
Autymate No 
Azure Data Lake Yes 
Data Sentinel No 
Gable No 
Google Cloud Storage Yes 
Gravity Data No 
MLJAR Studio No 
Meltano No 
OpenObserve No 
PuppyGraph No 
QuerySurge No 
SDF No 
Semarchy xDI No 
Streamkap No 
Tenzir No 
Tictable No 
Timbr.ai No 
Tonic Ephemeral No 
Warp 10 No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$5 per TB
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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) No 
In Person Yes 

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

parquet.apache.org

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

docs.cloud.google.com/lakehouse/docs

Product Features

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 

Alternatives

Alternatives

Archon Data Store Reviews

Archon Data Store

Platform 3 Solutions
Apache Iceberg Reviews

Apache Iceberg

Apache Software Foundation
Apache HBase Reviews

Apache HBase

The Apache Software Foundation