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What is Oracle Data Service Integrator?

Oracle Data Service Integrator enables organizations to quickly establish and manage federated data services, providing a seamless way to access various datasets. Built entirely on industry standards, this tool is designed to be declarative and encourages the reuse of data services. It uniquely serves as the only data federation solution that allows for the creation of bidirectional data services that support both reading and writing across multiple data sources. In addition, it features a groundbreaking capability that eliminates the need for coding, allowing users to graphically design both simple and complex adjustments to different data sources with ease. Users benefit from straightforward installation, validation, uninstallation, upgrading, and initiation processes with the Data Service Integrator. Originally known as Liquid Data and AquaLogic Data Services Platform (ALDSP), Oracle Data Service Integrator still includes some elements from these previous titles in its product architecture, installation paths, and components. This approach provides continuity for users who are accustomed to the legacy names, facilitating a smooth navigation experience within the system while enhancing overall functionality. As a result, organizations can maximize their data integration capabilities efficiently and effectively.

What is Oracle Cloud Infrastructure Data Lakehouse?

A data lakehouse embodies a modern, open architecture tailored for the storage, understanding, and analysis of large data sets. It combines the strong features of traditional data warehouses with the considerable adaptability provided by popular open-source data technologies currently in use. Building a data lakehouse is feasible on Oracle Cloud Infrastructure (OCI), which supports effortless integration with advanced AI frameworks and pre-built AI services, including Oracle’s language processing tools. Users can utilize Data Flow, a serverless Spark service, enabling them to focus on their Spark tasks without the hassle of infrastructure management. Many clients of Oracle seek to create advanced analytics driven by machine learning, applicable to their Oracle SaaS data or other SaaS sources. In addition, our intuitive data integration connectors simplify the setup of a lakehouse, promoting comprehensive analysis of all data alongside your SaaS information and considerably speeding up the solution delivery process. This groundbreaking methodology not only streamlines data governance but also significantly boosts analytical prowess for organizations aiming to harness their data more efficiently. Ultimately, the integration of these technologies empowers businesses to make data-driven decisions with greater agility and insight.

Media

Media

Integrations Supported

Docker
Kubernetes
NLSQL
RunMyJobs by Redwood

Integrations Supported

Docker
Kubernetes
NLSQL
RunMyJobs by Redwood

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/middleware/technologies/data-service-integrator.html

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/data-lakehouse/

Categories and Features

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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