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features
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support

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Description

Effortlessly extract, transform, and load (ETL) data for analytics and data science applications. Create seamless, code-free data flows directed towards data lakes and data marts. This functionality is included within Oracle’s extensive suite of integration tools. The user-friendly interface allows for easy configuration of integration parameters and automates the mapping of data between various sources and targets. You can utilize pre-built operators like joins, aggregates, or expressions to effectively manipulate your data. Central management of your processes enables the use of parameters to adjust specific configuration settings during runtime. Users can actively prepare their datasets and observe transformation results in real-time for process validation. Enhance your productivity and adjust data flows instantly, without needing to wait for execution completion. Additionally, this solution helps prevent broken integration flows and minimizes maintenance challenges as data schemas change over time, ensuring a smooth data management experience. This capability empowers users to focus on gaining insights from their data rather than grappling with technical difficulties.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Bing No 
Google Ads No 
Google Cloud BigQuery No 
Google Sheets No 
Harvest No 
Harvest Forecast No 
Klaviyo No 
Lever No 
Mailshake No 
Mambu No 
Meta Ads No 
Onfleet No 
Oracle Cloud Infrastructure Yes 
Ortto No 
Pepperjam No 
PostgreSQL No 
Purple No 
SurveyMonkey No 
Trello No 
Yotpo No 

Integrations

Bing Yes 
Google Ads Yes 
Google Cloud BigQuery Yes 
Google Sheets Yes 
Harvest Yes 
Harvest Forecast Yes 
Klaviyo Yes 
Lever Yes 
Mailshake Yes 
Mambu Yes 
Meta Ads Yes 
Onfleet Yes 
Oracle Cloud Infrastructure No 
Ortto Yes 
Pepperjam Yes 
PostgreSQL Yes 
Purple Yes 
SurveyMonkey Yes 
Trello Yes 
Yotpo Yes 

Pricing Details

$0.04 per GB per hour
Free Trial Yes 
Free Version No 

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 Yes 
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 No 

Types of Training

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

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/integration/oracle-cloud-infrastructure-data-integration/

Vendor Details

Company Name

Singer

Website

www.singer.io

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Integration

Dashboard No 
ETL - Extract / Transform / Load No 
Metadata Management No 
Multiple Data Sources No 
Web Services No 

Product Features

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Alternatives

Alternatives