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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Oracle vs Riak

Oracle vs Riak

OverviewDecisionsComparisonAlternatives

Overview

Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
Riak
Riak
Stacks103
Followers137
Votes44
GitHub Stars4.0K
Forks535

Oracle vs Riak: What are the differences?

Introduction

In this article, we will discuss the key differences between Oracle and Riak databases.

  1. Data Model: Oracle is a relational database management system (RDBMS) that uses the structured query language (SQL) to organize and manipulate data in a tabular format. It follows the ACID (Atomicity, Consistency, Isolation, Durability) properties. On the other hand, Riak is a distributed NoSQL key-value database that allows for flexible and schemaless data models. It can store unstructured, semi-structured, and structured data without the need for predefined schemas.

  2. Scalability: Oracle databases are typically vertically scalable, meaning they can handle increased workload by adding more resources to a single server. However, this can be limited and may result in performance bottlenecks. Riak, on the other hand, is horizontally scalable, allowing for easy distribution of data across multiple servers, resulting in improved performance and handling of large-scale data.

  3. Consistency Model: Oracle enforces strong consistency in its database transactions, ensuring that data is always in a consistent state. It follows a single-copy consistency model where all operations on the database are sequentially consistent. Riak, however, adopts an eventual consistency model, where data changes may propagate asynchronously and may temporarily exist in different states across different nodes. This allows for high availability and fault tolerance but sacrifices strong consistency.

  4. Data Replication: Oracle databases typically use traditional master-slave replication methods for achieving high availability and data redundancy. Changes made on the master are replicated to one or more slaves. Riak, on the other hand, uses a distributed data replication model called multi-datacenter replication. This replicates data across multiple geographically distributed data centers, ensuring data availability, fault tolerance, and disaster recovery capabilities.

  5. Transaction Support: Oracle databases offer full ACID transactional support, ensuring that transactions are atomic, consistent, isolated, and durable. This provides data integrity and reliability in critical business applications. Riak, being a NoSQL database, may offer different transactional capabilities depending on the specific implementation or version used. While it may support relaxed transactional models, it may not provide full ACID compliance in all scenarios.

  6. Query Language: Oracle databases primarily use SQL as the query language for data retrieval and manipulation. SQL offers a rich set of declarative commands and advanced query optimization capabilities. Riak, being a NoSQL database, may offer different query languages depending on the specific implementation or version used. Some implementations may support SQL-like languages, while others may provide proprietary query languages optimized for key-value access or distributed querying.

In summary, Oracle is a relational database management system that follows a structured data model, strong consistency, and ACID transactional support. Riak, on the other hand, is a distributed NoSQL database with a schemaless data model, eventual consistency, and horizontal scalability. It offers flexible data storage, multi-datacenter replication, and may have varying transactional and query capabilities depending on the specific implementation used.

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Advice on Oracle, Riak

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
Riak
Riak

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.

Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.

Statistics
GitHub Stars
-
GitHub Stars
4.0K
GitHub Forks
-
GitHub Forks
535
Stacks
2.6K
Stacks
103
Followers
1.8K
Followers
137
Votes
113
Votes
44
Pros & Cons
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 5
    Expensive
Cons
  • 14
    Expensive
Pros
  • 14
    High Performance
  • 11
    High Availability
  • 9
    Easy Scalability
  • 5
    Flexible
  • 1
    Distributed

What are some alternatives to Oracle, Riak?

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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