Software Alternatives, Accelerators & Startups

GraphQL Cache VS Google Cloud Datastore

Compare GraphQL Cache VS Google Cloud Datastore and see what are their differences

GraphQL Cache logo GraphQL Cache

GraphQL provides a complete description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

Google Cloud Datastore logo Google Cloud Datastore

Cloud Datastore is a NoSQL database for your web and mobile applications.
  • GraphQL Cache Landing page
    Landing page //
    2023-08-29
  • Google Cloud Datastore Landing page
    Landing page //
    2023-09-12

GraphQL Cache features and specs

No features have been listed yet.

Google Cloud Datastore features and specs

  • Scalability
    Google Cloud Datastore can automatically scale to handle large amounts of data and high read/write loads, making it suitable for applications with growing data needs.
  • Fully Managed
    As a fully managed service, Google Cloud Datastore eliminates the need for managing servers, software patches, and replication, allowing developers to focus on building applications.
  • High Availability
    Datastore provides strong consistency for reads and writes and is designed to maintain availability even in case of entire data center outages.
  • Flexible Data Model
    The schemaless nature of Datastore allows for a flexible data model that can easily adapt to changes in application requirements.
  • Integration with Google Cloud Platform
    Datastore seamlessly integrates with other Google Cloud Platform services, which simplifies the process of building end-to-end solutions.

Possible disadvantages of Google Cloud Datastore

  • Complex Query Language
    Datastore Query Language (GQL) can be less intuitive compared to SQL, which may pose a learning curve for developers accustomed to traditional relational databases.
  • Eventual Consistency for Queries
    While Datastore offers strong consistency for entity lookups by key, queries must be specifically configured for strong consistency, otherwise they might return eventually consistent data.
  • Cost
    As usage scales, costs can increase, particularly for applications with high write loads or those requiring many transactional operations, which might be a consideration for budget-conscious projects.
  • Limited Relational Capabilities
    Datastore is a NoSQL database, which means it lacks some of the relational features like joins and complex transactions that developers might expect from a SQL database.
  • Index Management
    Managing indexes can become complex, as every query in Datastore requires a corresponding index, and poorly planned indexes can lead to increased storage costs and slower query performance.

Analysis of GraphQL Cache

Overall verdict

  • GraphQL is an excellent and mature query language for APIs, and its caching capabilitiesโ€”while more nuanced than RESTโ€”are well-supported through client libraries and normalized caches that make it a solid choice for modern applications.

Why this product is good

  • Client-side normalized caching (via tools like Apollo Client and Relay) allows efficient data storage and retrieval by unique identifiers, reducing redundant network requests
  • Enables precise data fetching so clients only request and cache exactly the fields they need, minimizing over-fetching and cache bloat
  • Strong ecosystem support with well-documented caching strategies and persisted queries that can leverage HTTP and CDN caching
  • Automatic cache updates and consistency management keep UI data in sync after mutations
  • Backed by a large community and official documentation at graphql.org that clearly explains caching approaches

Recommended for

  • Applications with complex, nested data requirements where over-fetching is a concern
  • Teams building rich client-side apps using Apollo Client or Relay that benefit from normalized caching
  • Developers who need fine-grained control over what data is fetched and cached
  • Projects with multiple frontend clients (web, mobile) consuming the same flexible API
  • Organizations wanting to reduce network payloads and improve perceived performance through smart client caching

Category Popularity

0-100% (relative to GraphQL Cache and Google Cloud Datastore)
API
100 100%
0% 0
Databases
14 14%
86% 86
NoSQL Databases
11 11%
89% 89
Network & Admin
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Google Cloud Datastore should be more popular than GraphQL Cache. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

GraphQL Cache mentions (4)

  • What are the Differences between GQL and REST?
    'id' data type and field to help support caching: https://graphql.org/learn/caching/. Source: over 3 years ago
  • GraphQL Is a Trap?
    > Take a look at this. I repeat: client-side caching is not a problem, even with GraphQL. The technical problems regarding GraphQL's blockers to caching lies in server-side caching. For server-side caching, the only answer that GraphQL offers is to use primary keys, hand-wave a lot, and hope that your GraphQL implementation did some sort of optimization to handle that corner case by caching results. Don't take my... - Source: Hacker News / about 4 years ago
  • GraphQL Is a Trap?
    > Checkout Relay.js: https://relay.dev/ Relay is a GraphQL client. That's the irrelevant side of caching, because that can be trivially implemented by an intern, specially given GraphQL's official copout of caching based on primary keys [1], and doesn't have any meaningful impact on the client's resources. The relevant side of caching is server-side caching: the bits of your system that allow it to fulfill... - Source: Hacker News / about 4 years ago
  • Designing a URL-based query syntax for GraphQL
    This is clever! Can anyone help me understand how this lines up with the original value proposition of GraphQL? I was under the impression that the Big Idea behind GraphQL was, amongst other things, client-side caching[1]. Iโ€™m probably missing some nuance here, so bear with me: if your GraphQL client is caching properly, then what would this syntax give a developer that a URL query parameter parser couldnโ€™t? [1]... - Source: Hacker News / about 5 years ago

Google Cloud Datastore mentions (7)

  • Using Google Cloud Firestore with Django's ORM
    A long time ago, a fork of Django called โ€œDjango-nonrelโ€ experimented with the idea of using Djangoโ€™s ORM with a non-relational database; what was then called the App Engine Datastore, but is now known as Google Cloud Datastore (or technically, Google Cloud Firestore in Datastore Mode). Since then a more recent project called "django-gcloud-connectors" has been developed by Potato to allow seamless ORM integration... - Source: dev.to / about 2 years ago
  • How to deploy flask app with sqlite on google cloud ?
    In that case use Cloud Datastore (aka Firestore in Datastore Mode). It's a NoSQL db that was initially targeted just for GAE (you needed to have a GAE App even if empty to use it) but that requirement has been relaxed. Source: over 3 years ago
  • Is Cloud Run a good choice for a portfolio website?
    As u/SierraBravoLima said - If you don't really need containerization, you can go with Google App Engine (Standard). If you need to store data, GAE will work with cloud datastore which has a large enough free tier. Source: about 4 years ago
  • Help! Difference between native and datastore
    Datastore mode had its start in App Engine's early days (launched in 2008), where its Datastore was the original scalable NoSQL database provided for all App Engine apps. In 2013, Datastore was made available all developers outside of App Engine, and "re-launched" as Cloud Datastore. In 2014, Google acquired Firebase for its RTDB (real-time database). Both teams worked together for the next 4 years, and in 2017,... Source: over 4 years ago
  • I'm a dev ID 10 T please help me
    Database: datastore should be very cheap, or you could just output as csv text and copy into Google Sheets (free!). Source: over 4 years ago
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What are some alternatives?

When comparing GraphQL Cache and Google Cloud Datastore, you can also consider the following products

ZeroSSL - FREE SSL certificates issued instantly online with Free SSL Certificate Wizard.

MarkLogic Server - MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities.

Let's Encrypt - Letโ€™sย Encrypt is a free, automated, and open certificate authority brought to you by the Internet Security Research Group (ISRG).

Datomic - The fully transactional, cloud-ready, distributed database

Ehcache - Java's most widely used cache.

Valentina Server - Valentina Server is 3 in 1: Valentina DB Server / SQLite Server / Report Server