Compare Hevo vs Foghub

Summary

Hevo Data is a no-code, bi-directional data pipeline platform specially built for modern ETL, ELT, and Reverse ETL Needs. It helps data teams streamline and automate org-wide data flows that result in a saving of ~10 hours of engineering time/week and 10x faster reporting, analytics, and decision making. The platform supports 100+ ready-to-use integrations across Databases, SaaS Applications, Cloud Storage, SDKs, and Streaming Services. Over 500 data-driven companies spread across 35+ countries trust Hevo for their data integration needs. Try Hevo today and get your fully managed data pipelines up and running in just a few minutes. ..show more

Foghub is a platform that offers its users with critical-path to IT/OT convergence, connecting sensors, devices, and systems with people, processes, and applications hence enabling automatic data acquisition, data engineering, transformations, advanced analytics, and ML. The software allows for its users to handle wide variety, volume, and velocity of industrial data with out of the box support for all data types, popular industrial network protocols, OT/lab systems, and databases. The easy to use fully configurable data flows to ensure the data remains available and usable by business stakeholders, when and where they want it in the system of their choice. Foghub enables its users to turbocharge existing business/IT systems with data, directly from the source of truth securely and transparently. The software offers an out of the box integration with most popular industrial network communication protocols, databases, cloud platforms, enterprise systems such as ERM, EAM, CRM, and CMMS, SaaS applications, messaging and communication platforms. ..show more

API Integration It allows easy integration of logic or data with other software application.

Compliance Tracking Helps in tracking and monitoring and auditing all the regulatory compliance requirements

Data Analysis Helps in analyzing stored raw data and converting them into useful reports

Data Extraction Helps in extracts the data from different databases and files

Data Filtering Helps in refining the data into datasets to form strategic groups

Data Integration Helps in collecting and combining data from multiple data sources and offer them in a unified manner to the user

Data Quality Control Helps in monitoring the quality of data input and processed

Data Transformation It helps in formatting the extracted data as specified in the target format.

Managed File Transfers Ad-hoc file transfers solution using FTP, HTTP, and etc.

Master Data Management Enables an organization to manage and integrate all of its critical corporate to a centralized point of reference

Match & Merge Helps matching data across multiple sources and to merge them for offering a better view to the data managers

Metadata Management Helps in administering and managing the data that describes other data

Version Control It gives the team the ability to recall specific versions of a document, code, content, file, or folder that records changes over time.

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Rivery