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An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism
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What is Oracle?

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
Oracle is a tool in the Databases category of a tech stack.

Who uses Oracle?

283 companies reportedly use Oracle in their tech stacks, including Netflix, LinkedIn, and ebay.

1667 developers on StackShare have stated that they use Oracle.

Oracle Integrations

Slick, Entity Framework, MSSQL, Oracle PL/SQL, and Liquibase are some of the popular tools that integrate with Oracle. Here's a list of all 124 tools that integrate with Oracle.
Pros of Oracle
High Availability
Hard to maintain
Hard to use
High complexity
Decisions about Oracle

Here are some stack decisions, common use cases and reviews by companies and developers who chose Oracle in their tech stack.

I recently started a new position as a data scientist at an E-commerce company. The company is founded about 4-5 years ago and is new to many data-related areas. Specifically, I'm their first data science employee. So I have to take care of both data analysis tasks as well as bringing new technologies to the company.

  1. They have used Elasticsearch (and Kibana) to have reporting dashboards on their daily purchases and users interactions on their e-commerce website.

  2. They also use the Oracle database system to keep records of their daily turnovers and lists of their current products, clients, and sellers lists.

  3. They use Data-Warehouse with cockpit 10 for generating reports on different aspects of their business including number 2 in this list.

At the moment, I grab batches of data from their system to perform predictive analytics from data science perspectives. In some cases, I use a static form of data such as monthly turnover, client values, and high-demand products, and run my predictive analysis using Python (VS code). Also, I use Google Datastudio or Google Sheets to present my findings. In other cases, I try to do time-series analysis using offline batches of data extracted from Elastic Search to do user recommendations and user personalization.

I really want to use modern data science tools such as Apache Spark, Google BigQuery, AWS, Azure, or others where they really fit. I think these tools can improve my performance as a data scientist and can provide more continuous analytics of their business interactions. But honestly, I'm not sure where each tool is needed and what part of their system should be replaced by or combined with the current state of technology to improve productivity from the above perspectives.

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Dishi Jain
Needs advice

So we are re-engineering our application database to make it cloud-native and deploy on the Kubernetes platform. Currently, our data lies on the Oracle 19c database and it is normalized extensively. We store pdfs, txt files and allow a user to edit, delete, view, create new transactions. Now I want to pick a DB, which makes the re-engineering, not a big deal but allows us to store data in a distributed manner on Kubernetes. Please assist me.

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Hello guys! I would ask for your advice. Our situation is like that there will be a project to revamp workflows and introduce new services like mobile apps, machine learning, and some online services that would use cloud storage. We use JSF, JavaScript, Ajax, Spring, Oracle 12c running on Linux (VM) and providing online services to internal users and the public. But, we are not technically savvy enough to evaluate what tools should be introduced. Personally, I am evaluating whether to take this opportunity to change our practice/PM approach from Prince to Scrum/Agile (It seemed that DevOps is popular) ... Since we adopt ISO 27001 and ISO 20000, security is a crucial factor that we consider. Would you please help to recommend a list of tools and explain the reasons why you recommend them? Thanks in advance~!

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Needs advice

Hi. We are planning to develop web, desktop, and mobile app for procurement, logistics, and contracts. Procure to Pay and Source to pay, spend management, supplier management, catalog management. ( similar to SAP Ariba,,,,

We got stuck when deciding which technology stack is good for the future. We look forward to your kind guidance that will help us.

We want to integrate with multiple databases with seamless bidirectional integration. What APIs and middleware available are best to achieve this? SAP HANA, Oracle, MySQL, MongoDB...

ASP.NET / Node.js / Laravel. ......?

Please guide us

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Needs advice

Hi, Which RDBMS can replace Oracle when it comes to high availability & heavy transactional load with zero RTO & RPO.

Thanks, G

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Saurav Pandit
Application Devloper at Bny Mellon · | 9 upvotes · 292.3K views

I have just started learning Python 3 week back. I want to create REST api using python. The api will be use to save form data in Oracle database. The front end is using AngularJS 8 with Angular Material. In python there are so many framework for developing REST ** I am looking for some suggestions which REST framework to choose? ** Here are some feature I am looking for * Easy integration and unit testing like in Angular we just run command. * Code packageing, like in Java maven project we can build and package. I am looking for something which I can push in artifactory and deploy whole code as package. *Support for swagger/ OpenAPI * Support for JSON Web Token * Support for testcase coverage report Framework can have feature included or can be available by extension.

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Oracle Alternatives & Comparisons

What are some alternatives to Oracle?
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
Workday is a leading provider of enterprise cloud applications for human resources and finance. Founded in 2005, Workday delivers human capital management, financial management, and analytics applications designed for the world’s largest organizations. Hundreds of companies, ranging from medium-sized businesses to Fortune 50 enterprises, have selected Workday.
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
Prophet is a procedure for forecasting time series data. It is based on an additive model where non-linear trends are fit with yearly and weekly seasonality, plus holidays. It works best with daily periodicity data with at least one year of historical data. Prophet is robust to missing data, shifts in the trend, and large outliers.
DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.
See all alternatives

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