Google Cloud Spanner vs Oracle

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Google Cloud Spanner

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Google Cloud Spanner vs Oracle: What are the differences?

Introduction

Google Cloud Spanner and Oracle are two popular database management systems that offer a range of features for storing and managing data. While both systems have similarities, they also have key differences that set them apart. In this article, we will explore these differences to help you understand which system may be better suited for your specific needs.

  1. Scalability: One of the key differences between Google Cloud Spanner and Oracle is their scalability capabilities. Google Cloud Spanner is designed to be highly scalable, allowing you to scale your database horizontally across multiple servers and regions. This means that as your data and workload increase, you can easily expand your infrastructure to handle the load. On the other hand, Oracle traditionally relies on vertical scalability, where you can vertically add more resources to a single server to handle the increased workload. This difference in scalability approach can have implications on the cost and performance of each system.

  2. Consistency Model: Another significant difference between Google Cloud Spanner and Oracle is their consistency model. Google Cloud Spanner follows a globally consistent, distributed transaction model. This means that all reads and writes are guaranteed to be seen across all regions in a coherent and consistent manner. On the other hand, Oracle provides a more flexible consistency model, allowing you to configure different levels of consistency based on your specific requirements. This difference in consistency models can be crucial depending on the nature of your data and applications.

  3. Architecture: The architecture of Google Cloud Spanner and Oracle also differs significantly. Google Cloud Spanner is a globally distributed relational database that uses a shared-nothing architecture. This means that data is distributed across multiple nodes or servers, and each node operates independently. On the other hand, Oracle uses a shared-everything architecture, where all nodes share a common set of resources. This architectural difference affects the performance, scalability, and fault-tolerance capabilities of each system.

  4. Deployment Options: Google Cloud Spanner and Oracle offer different deployment options. Google Cloud Spanner is a fully managed database service that is provided by Google, meaning you don't have to worry about managing the infrastructure and can focus on your applications. Oracle, on the other hand, provides both on-premises and cloud-based deployment options, giving you more flexibility and control over your infrastructure. The choice of deployment option can depend on factors such as security, compliance, and organizational preferences.

  5. Pricing Model: The pricing model of Google Cloud Spanner and Oracle also differs. Google Cloud Spanner offers a pricing model based on the amount of storage, network egress, and processing resources used. This can provide more predictable and transparent pricing, especially for organizations with variable or unpredictable workloads. Oracle, on the other hand, often follows a more traditional licensing model, where you pay for the number of cores or processors, which can result in more complex pricing structures.

  6. Ecosystem and Integration: The ecosystems and integration capabilities of Google Cloud Spanner and Oracle are also worth considering. Oracle has been in the market for a long time and has a large ecosystem of products, tools, and third-party integrations. This can be beneficial if you are already using other Oracle products or have specific integration requirements. Google Cloud Spanner, on the other hand, is part of the broader Google Cloud Platform ecosystem, which offers a wide range of services and integrations with other Google Cloud services. Understanding the ecosystem and integration options can help you choose the system that fits well into your existing technology stack.

In summary, Google Cloud Spanner and Oracle have key differences in terms of scalability, consistency model, architecture, deployment options, pricing model, and ecosystem/integration capabilities. Understanding these differences can help you make an informed decision based on your specific needs and requirements.

Decisions about Google Cloud Spanner and Oracle
Daniel Moya
Data Engineer at Dimensigon · | 4 upvotes · 464.6K 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 Google Cloud Spanner
Pros of Oracle
  • 1
    Strongly consistent
  • 1
    Horizontal scaling
  • 1
    Scalable
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 5
    Expensive
  • 4
    Maintainable
  • 4
    Hard to use
  • 3
    High complexity

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Cons of Google Cloud Spanner
Cons of Oracle
    Be the first to leave a con
    • 14
      Expensive

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    What is Google Cloud Spanner?

    It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.

    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 Google Cloud Spanner?
    What companies use Oracle?
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    What tools integrate with Google Cloud Spanner?
    What tools integrate with Oracle?

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    What are some alternatives to Google Cloud Spanner and Oracle?
    Google Cloud SQL
    Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.
    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.
    Google Cloud Datastore
    Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
    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.
    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