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NuoDB

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NuoDB vs Oracle: What are the differences?

1. Architecture: NuoDB follows a peer-to-peer architecture with nodes working together in a mesh network, whereas Oracle utilizes a client-server architecture with a central database server and clients connecting to it. 2. Scaling: NuoDB provides elastic scalability, allowing for the addition of nodes to handle increased workloads, while Oracle requires manual partitioning and sharding to scale. 3. Consistency: NuoDB offers immediate consistency, ensuring that all nodes see the same data at the same time, whereas Oracle allows for eventual consistency, where there may be a delay in data synchronization across nodes. 4. SQL Compatibility: NuoDB supports SQL standards and is MySQL compatible, making it easier for developers familiar with traditional databases, while Oracle has its SQL variant and may require additional training for developers. 5. License Model: NuoDB follows a subscription-based pricing model, providing flexibility in licensing options, whereas Oracle has a more traditional license fee structure that can be costly for organizations. 6. High Availability: NuoDB includes built-in data redundancy and failover mechanisms for high availability, whereas Oracle requires additional configuration and setup for achieving similar levels of availability.

In Summary, NuoDB and Oracle differ in their architecture, scalability, consistency, SQL compatibility, license model, and high availability features.

Decisions about NuoDB and Oracle
Daniel Moya
Data Engineer at Dimensigon · | 4 upvotes · 421.3K views

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.

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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.

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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.

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Pros of NuoDB
Pros of Oracle
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    • 44
      Reliable
    • 33
      Enterprise
    • 15
      High Availability
    • 5
      Expensive
    • 5
      Hard to maintain
    • 4
      Maintainable
    • 4
      Hard to use
    • 3
      High complexity

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    Cons of NuoDB
    Cons of Oracle
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      • 14
        Expensive

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      What is NuoDB?

      NuoDB’s continuously available, ACID-compliant, SQL database delivers on-demand capacity on commodity hardware across multiple data centers.

      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.

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      What companies use NuoDB?
      What companies use Oracle?
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        What tools integrate with NuoDB?
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          What are some alternatives to NuoDB and Oracle?
          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.
          VoltDB
          VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.
          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.
          CockroachDB
          CockroachDB is distributed SQL database that can be deployed in serverless, dedicated, or on-prem. Elastic scale, multi-active availability for resilience, and low latency performance.
          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.
          See all alternatives