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ease
features
design
support

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Write a Review

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

Singer outlines the interaction between data extraction scripts, known as "taps," and data loading scripts referred to as "targets," facilitating their use in various combinations for transferring data from multiple sources to diverse destinations. This enables seamless data movement across databases, web APIs, files, queues, and virtually any other medium imaginable. The simplicity of Singer taps and targets is evident as they are designed as straightforward applications that utilize pipes—eliminating the need for complex daemons or plugins. Communication between Singer applications occurs through JSON, which enhances compatibility and ease of implementation across different programming languages. Additionally, Singer incorporates JSON Schema to ensure robust data types and structured organization when necessary. Another advantage of Singer is its ability to easily maintain state during consecutive runs, thereby enabling efficient incremental data extraction. This makes Singer not only versatile but also a powerful tool in the realm of data integration.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AppsFlyer
Beats
Braintree
Eloqua
Freshdesk
Google Analytics
Invoiced
Lever
Listrak
Mambu
Marigold Engage
Meta Ads
Pendo
Salesforce Agentforce Marketing
Salesforce Marketing Cloud Account Engagement
SendGrid
Stripe
Toggl Track
Typeform
Warp 10

Integrations

AppsFlyer
Beats
Braintree
Eloqua
Freshdesk
Google Analytics
Invoiced
Lever
Listrak
Mambu
Marigold Engage
Meta Ads
Pendo
Salesforce Agentforce Marketing
Salesforce Marketing Cloud Account Engagement
SendGrid
Stripe
Toggl Track
Typeform
Warp 10

Pricing Details

No price information available.
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

Apache Software Foundation

Founded

1999

Country

United States

Website

avro.apache.org

Vendor Details

Company Name

Singer

Website

www.singer.io

Product Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Product Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Alternatives

Alternatives

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