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features
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support

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Description

Apache Avro™ serves as a system for data serialization, offering intricate data structures and a fast, compact binary format along with a container file for persistent data storage and remote procedure calls (RPC). It also allows for straightforward integration with dynamic programming languages, eliminating the need for code generation when reading or writing data files or implementing RPC protocols; this only becomes a recommended optimization for statically typed languages. Central to Avro's functionality is its reliance on schemas, which accompany the data at all times, ensuring that the schema used for writing is always available during reading. This design choice minimizes the overhead per value, resulting in both rapid serialization and reduced file size. Furthermore, it enhances compatibility with dynamic and scripting languages since the data is entirely self-describing along with its schema. When data is saved in a file, its corresponding schema remains embedded within, allowing for subsequent processing by any compatible program. In instances where the reading program anticipates a different schema, this discrepancy can be resolved with relative ease, showcasing Avro's flexibility and efficiency in data management. Overall, Avro's architecture significantly streamlines the handling of data across a variety of programming environments.

Description

Data schemas define the structure and content of various types of information, such as blood glucose levels, influencing how software applications manage that information. Often, systems must accommodate data from multiple devices or platforms, each presenting information in its own unique way. When all data related to a specific metric, like blood glucose, adheres to a unified schema, it becomes significantly easier to analyze and interpret that information, regardless of its original source. A standardized schema acts as a consistent point of reference for documentation, facilitating the use of data points across different contexts. In the realm of healthcare, the importance of common data schemas is magnified due to the intricate nature and significance of health-related information. For instance, recognizing the difference between fasting and non-fasting blood glucose levels is crucial for accurate clinical interpretation and decision-making. This shared understanding ensures that healthcare professionals can communicate effectively and make informed decisions based on reliable data.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache DataFusion Yes 
Apache Hive Yes 
Arroyo Yes 
Beats Yes 
Data Sentinel Yes 
Hackolade Yes 
SSIS Integration Toolkit Yes 
Semarchy xDI Yes 
Specmatic Yes 
Timeplus Yes 
Tonic Ephemeral Yes 
Warp 10 Yes 
e6data Yes 

Integrations

Apache DataFusion No 
Apache Hive No 
Arroyo No 
Beats No 
Data Sentinel No 
Hackolade No 
SSIS Integration Toolkit No 
Semarchy xDI No 
Specmatic No 
Timeplus No 
Tonic Ephemeral No 
Warp 10 No 
e6data No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

avro.apache.org

Vendor Details

Company Name

Open mHealth

Country

United States

Website

www.openmhealth.org

Product Features

DevOps

Approval Workflow No 
Dashboard No 
KPIs No 
Policy Management No 
Portfolio Management No 
Prioritization No 
Release Management No 
Timeline Management No 
Troubleshooting Reports No 

Product Features

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