Overview

Oracle

Stacks2.4K

Followers1.8K

Votes113

Microsoft Access

Stacks81

Followers87

Votes0

Microsoft Access vs Oracle: What are the differences?

Key Differences between Microsoft Access and Oracle

Microsoft Access and Oracle are both popular database management systems used in various industries. While they share some similarities, there are several key differences that set them apart.

Scalability: One major difference between Microsoft Access and Oracle is their scalability. Microsoft Access is designed for small to medium-sized databases, while Oracle is highly scalable and can handle large amounts of data and high user loads. This makes Oracle better suited for enterprise-level applications with high data volumes and complex requirements.
Data security: Another significant difference is in their data security capabilities. Oracle provides advanced security features, such as fine-grained access controls, encryption, and robust authentication mechanisms. On the other hand, Microsoft Access has limited security options, making it less suitable for applications that require stringent data protection.
Concurrency control: Oracle offers sophisticated concurrency control mechanisms, allowing multiple users to access and modify the data simultaneously without conflicts. In contrast, Microsoft Access has weaker concurrency control capabilities, which can lead to data integrity issues when multiple users are working on the same database simultaneously.
Support for programming languages: Oracle supports multiple programming languages, including SQL, PL/SQL, Java, and others, making it more versatile and flexible in terms of application development. Microsoft Access primarily uses its proprietary programming language, VBA (Visual Basic for Applications), which limits the range of programming options available.
Cross-platform compatibility: Oracle is designed to run on various operating systems, including Windows, Linux, and Unix, offering greater flexibility in terms of platform choice. Microsoft Access, on the other hand, is limited to the Windows platform, which can be a constraint for organizations using different operating systems.
Cost: While both Microsoft Access and Oracle have their respective licensing costs, Oracle tends to be more expensive, especially for larger deployments and enterprise-level solutions. Microsoft Access, on the other hand, is often bundled with other Microsoft Office products, making it a more affordable option for small-scale applications.

In summary, Oracle is a robust and scalable database management system with advanced security and concurrency control capabilities, suitable for enterprise-level applications and large data volumes. Microsoft Access, on the other hand, is more suitable for small to medium-sized databases and offers a more affordable option for simple applications with limited security and scalability requirements.

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Advice on Oracle, Microsoft Access

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

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

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	Microsoft Access
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 an easy-to-use tool for creating business applications, from templates or from scratch. With its rich and intuitive design tools, it can help you create appealing and highly functional applications in a minimal amount of time.
-	rich and intuitive design tools; highly functional applications in a minimal amount of time
Statistics
Stacks 2.4K	Stacks 81
Followers 1.8K	Followers 87
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	Microsoft SQL Server Azure SQL Database

What are some alternatives to Oracle, Microsoft Access?

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

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

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

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 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

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 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

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.