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ease
features
design
support

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Write a Review

Description

Concentrate on producing insightful and impactful reports and analytics rather than getting bogged down in the complexities of data warehouse code. Avoid allowing your data warehouse to turn into a chaotic mix of numerous difficult-to-manage pipelines, notebooks, stored procedures, tables, and views. Dimodelo DW Studio significantly minimizes the workload associated with designing, constructing, deploying, and operating a data warehouse. It enables the design and deployment of a data warehouse optimized for Azure Synapse Analytics. By creating a best practice architecture that incorporates Azure Data Lake, Polybase, and Azure Synapse Analytics, Dimodelo Data Warehouse Studio ensures the delivery of a high-performance and contemporary data warehouse in the cloud. Moreover, with its use of parallel bulk loads and in-memory tables, Dimodelo Data Warehouse Studio offers an efficient solution for modern data warehousing needs, enabling teams to focus on valuable insights rather than maintenance tasks.

Description

lakeFS allows you to control your data lake similarly to how you manage your source code, facilitating parallel pipelines for experimentation as well as continuous integration and deployment for your data. This platform streamlines the workflows of engineers, data scientists, and analysts who are driving innovation through data. As an open-source solution, lakeFS enhances the resilience and manageability of object-storage-based data lakes. With lakeFS, you can execute reliable, atomic, and versioned operations on your data lake, encompassing everything from intricate ETL processes to advanced data science and analytics tasks. It is compatible with major cloud storage options, including AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). Furthermore, lakeFS seamlessly integrates with a variety of modern data frameworks such as Spark, Hive, AWS Athena, and Presto, thanks to its API compatibility with S3. The platform features a Git-like model for branching and committing that can efficiently scale to handle exabytes of data while leveraging the storage capabilities of S3, GCS, or Azure Blob. In addition, lakeFS empowers teams to collaborate more effectively by allowing multiple users to work on the same dataset without conflicts, making it an invaluable tool for data-driven organizations.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Kinesis
Amazon S3
Amazon Web Services (AWS)
Apache Flink
Apache Spark
Astro by Astronomer
Azure Data Lake
Azure DevOps
Azure SQL Database
Azure Synapse Analytics
Databricks
Delta Lake
Google Cloud Storage
Hadoop
Looker
MLflow
Microsoft Azure
Microsoft Power BI
MinIO
Presto

Integrations

Amazon Kinesis
Amazon S3
Amazon Web Services (AWS)
Apache Flink
Apache Spark
Astro by Astronomer
Azure Data Lake
Azure DevOps
Azure SQL Database
Azure Synapse Analytics
Databricks
Delta Lake
Google Cloud Storage
Hadoop
Looker
MLflow
Microsoft Azure
Microsoft Power BI
MinIO
Presto

Pricing Details

$899 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Dimodelo

Country

Australia

Website

www.dimodelo.com

Vendor Details

Company Name

Treeverse

Founded

2020

Country

Israel

Website

lakefs.io

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Alternatives

Alternatives