Provide a virtual layer of data abstraction, allow data to be accessed and integrated in real-time.
Provide a virtual layer of data abstraction, allowing for real-time data access and integration. Enables immediate insights, promotes system responsiveness, and enhances data availability.
We’ve listed the products and solutions that commonly address the Data Virtualization use case below.
Denodo offers a data virtualization and data integration platform.
Talend offers a unified suite of apps to collect, govern, transform, and share data.
Palantir Foundry is a platform that removes the barriers between back-end data management and front-end data analysis.
Pentaho is a comprehensive platform for data integration and business analytics.
Qlik is a data integration and data analytics platform.
AWS Glue is a managed ETL service from Amazon that organizes, cleans, and loads data from various sources.
Google Cloud Data Fusion is a fully managed data integration platform enabling data ingestion, ETL, and real-time capabilities.
Hevo is a zero-maintenance data pipeline platform automating data sync from various sources to warehouses, simplifying analytics for data teams.
Meltano is an open-source platform for orchestrating ELT pipelines, enabling data teams to fetch, send, and transform data effortlessly.
Fivetran is a fully-managed, zero-maintenance cloud-based data pipeline.
Informatica offers a cloud-based data integration solution providing automated capabilities for ETL, ELT and replication.
Azure Data Factory is a data integration service that helps in constructing ETL/ELT processes.
SnapLogic is an intelligent integration platform with a visual interface for integrating apps and data.
Matillion is a cloud-native platform for data integration, transformation, and quality.
StreamSets by Software AG is an end-to-end data integration platform designed for dataOps.
Customize these feature priorities in Taloflow and get expert ratings for 15 different vendors and solutions, including None.
| Feature | Dimensions | Description | Priority |
|---|---|---|---|
| Data Encryption |
|
Protects data confidentiality by converting it to encoded form. | Critical |
| Data Federation |
|
Integrates data from disparate sources by creating a virtual database that provides a unified view of the data. | Critical |
| Data Source Auto-detection |
|
It automatically detects and connects to various data sources, simplifying the data integration setup process. | Critical |
| Data Virtualization |
|
Creates in-memory virtualized views from data in disparate sources. | Critical |
| Schema Evolution |
|
Manages schema changes in data sources, ensuring seamless integration and adaptability to evolving data structures. | Critical |
| Audit Trails |
|
Provides audit trails to track changes made to data during the integration process. | Important |
| Data Cataloging |
|
It can natively provide an inventory of data assets in the organization or integrate with other data cataloging tools. | Important |
| Data Masking |
|
Masks your data while it's in motion. | Important |
| Role Based Access Control (RBAC) |
|
Authorizes and restricts access to specific functions based on the user's role within the organization. | Important |
| Transport Layer Security (TLS) |
|
Enables transport layer security for secure server communication. | Important |
| Data Transformation |
|
Ensures data consistency and quality by transforming, cleansing, and normalizing data. | Nice To Have |
| Real-time Data Delivery |
|
Ability to deliver near-real time data required for analysis. | Nice To Have |
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