Collect and integrate real-time data for real-time analysis, enable real-time decision making.
Collect and integrate real-time data for immediate analysis, promoting real-time decision-making. Aids rapid response to business changes and enhances operational agility.
We’ve listed the products and solutions that commonly address the Real-time Analytics 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 Extraction |
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Extracts data from various sources, including structured and unstructured data. | Critical |
| Data Transformation |
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Ensures data consistency and quality by transforming, cleansing, and normalizing data. | Critical |
| Data Visualization and Analytics |
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It provides built-in tools or compatibility with third-party tools for data visualization, reporting, and analytics. | Critical |
| Event-driven |
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Ability to execute data flows based on a relevant event. | Critical |
| Real-time Data Delivery |
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Ability to deliver near-real time data required for analysis. | Critical |
| Streaming Data Delivery |
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Ability to deliver streaming-oriented data movement or stream analysis. | Critical |
| Distributed Processing |
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Support is available for dividing data integration tasks into smaller sub-tasks, which can be processed simultaneously across multiple nodes. | Important |
| In Memory Processing |
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Support is available for in-memory processing through an in-memory database or cache to process large volumes of data. | Important |
| Containerization Support |
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Support is available for deploying and orchestrating using containers such as Docker and Kubernetes. | Nice To Have |
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