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  5. Oracle vs Veeva

Oracle vs Veeva

OverviewDecisionsComparisonAlternatives

Overview

Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
Veeva
Veeva
Stacks13
Followers12
Votes0

Oracle vs Veeva: What are the differences?

Introduction

In this article, we will discuss the key differences between Oracle and Veeva, two popular software systems used in different industries. These differences are important to consider when deciding on a suitable system for your organization.

  1. Integration Capabilities: Oracle offers comprehensive integration capabilities, allowing seamless connectivity between various systems within an organization. On the other hand, Veeva is specifically designed for the life sciences industry and provides built-in solutions tailored to the unique needs of pharmaceutical and biotech companies. This industry-specific focus enables Veeva to offer specialized integration features and functionalities that cater to the specific needs of life sciences businesses.

  2. Customizability: Oracle provides a high level of customizability in terms of system configuration and modules. Organizations can adapt Oracle to align with their specific business processes and requirements. In contrast, Veeva is built on a more structured architecture and offers limited customization options. This structured approach ensures regulatory compliance and enables rapid implementation but may limit flexibility for organizations with highly unique or complex workflows.

  3. Data Security and Compliance: Both Oracle and Veeva prioritize data security and compliance, but their approaches differ slightly. Oracle, being a general-purpose software platform, provides robust security features and complies with industry standards. Veeva, being industry-specific, has a strong focus on meeting the stringent regulatory requirements of the life sciences industry. It offers features such as built-in audit trails, electronic signature capabilities, and data encryption specifically designed for the pharmaceutical and biotech sectors.

  4. Industry Focus: Oracle caters to a wide range of industries and offers solutions that can be implemented across various sectors. It is not specifically tailored to any particular industry, which allows for versatility but might lead to less specialized functionality for specific verticals. In contrast, Veeva is solely focused on the life sciences industry. This industry-specific approach enables Veeva to offer tailored solutions, such as customer relationship management (CRM) software designed specifically for pharmaceutical sales and marketing teams.

  5. User Interface and User Experience: Oracle provides a comprehensive suite of business applications that can have a more complex user interface due to the vast number of features and functionalities it offers. Veeva, being industry-specific, has a more streamlined user interface that is specifically designed for the needs of life sciences professionals. This sector-focused design can enhance user experience by providing a simplified and intuitive interface tailored to the specific workflows and tasks performed in the life sciences industry.

  6. Cost Considerations: Oracle offers a range of products and pricing options to suit organizations of different sizes and budgets. The cost of Oracle implementation and maintenance could vary depending on the specific requirements and scale of the organization. Veeva, being a niche solution for the life sciences industry, may have a higher initial cost of implementation but can potentially provide a more cost-effective solution in the long run, considering its industry-specific functionality and reduced need for extensive customization.

In summary, Oracle provides a versatile, highly customizable software platform suitable for a wide range of industries, while Veeva offers specialized, industry-specific solutions tailored to the unique needs of the life sciences sector. Organizations should consider their specific industry requirements, integration capabilities, customization needs, and cost factors when choosing between Oracle and Veeva.

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Advice on Oracle, Veeva

Daniel
Daniel

Data Engineer at Dimensigon

Jul 18, 2020

Decided

We have chosen Tibero over Oracle because we want to offer a PL/SQL-as-a-Service that the users can deploy in any Cloud without concerns from our website at some standard cost. With Oracle Database, developers would have to worry about what they implement and the related costs of each feature but the licensing model from Tibero is just 1 price and we have all features included, so we don't have to worry and developers using our SQLaaS neither. PostgreSQL would be open source. We have chosen Tibero over Oracle because we want to offer a PL/SQL that you can deploy in any Cloud without concerns. PostgreSQL would be the open source option but we need to offer an SQLaaS with encryption and more enterprise features in the background and best value option we have found, it was Tibero Database for PL/SQL-based applications.

495k views495k
Comments
Abigail
Abigail

Dec 6, 2019

Decided

In the field of bioinformatics, we regularly work with hierarchical and unstructured document data. Unstructured text data from PDFs, image data from radiographs, phylogenetic trees and cladograms, network graphs, streaming ECG data... none of it fits into a traditional SQL database particularly well. As such, we prefer to use document oriented databases.

MongoDB is probably the oldest component in our stack besides Javascript, having been in it for over 5 years. At the time, we were looking for a technology that could simply cache our data visualization state (stored in JSON) in a database as-is without any destructive normalization. MongoDB was the perfect tool; and has been exceeding expectations ever since.

Trivia fact: some of the earliest electronic medical records (EMRs) used a document oriented database called MUMPS as early as the 1960s, prior to the invention of SQL. MUMPS is still in use today in systems like Epic and VistA, and stores upwards of 40% of all medical records at hospitals. So, we saw MongoDB as something as a 21st century version of the MUMPS database.

540k views540k
Comments
Abigail
Abigail

Dec 10, 2019

Decided

We wanted a JSON datastore that could save the state of our bioinformatics visualizations without destructive normalization. As a leading NoSQL data storage technology, MongoDB has been a perfect fit for our needs. Plus it's open source, and has an enterprise SLA scale-out path, with support of hosted solutions like Atlas. Mongo has been an absolute champ. So much so that SQL and Oracle have begun shipping JSON column types as a new feature for their databases. And when Fast Healthcare Interoperability Resources (FHIR) announced support for JSON, we basically had our FHIR datalake technology.

558k views558k
Comments

Detailed Comparison

Oracle
Oracle
Veeva
Veeva

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.

It is a CRM application built on the Salesforce platform designed specifically for the pharmaceutical and biotechnology industries. They are a leader in cloud-based software for the global life sciences industry.

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Route planning; Planograms for inventory monitoring; Order management integrated with CLM
Statistics
Stacks
2.6K
Stacks
13
Followers
1.8K
Followers
12
Votes
113
Votes
0
Pros & Cons
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 5
    Expensive
Cons
  • 14
    Expensive
No community feedback yet
Integrations
No integrations available
Auth0
Auth0
Segment
Segment
Intercom
Intercom
Marketo
Marketo
HubSpot
HubSpot
Zendesk
Zendesk
KISSmetrics
KISSmetrics
Datadog
Datadog

What are some alternatives to Oracle, Veeva?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

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.

PostgreSQL

PostgreSQL

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.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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