Software Alternatives, Accelerators & Startups

Datahike VS Cloud Functions for Firebase

Compare Datahike VS Cloud Functions for Firebase and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Datahike logo Datahike

A durable datalog database adaptable for distribution.

Cloud Functions for Firebase logo Cloud Functions for Firebase

Serverless / Task Processing
  • Datahike Landing page
    Landing page //
    2023-08-22
  • Cloud Functions for Firebase Landing page
    Landing page //
    2023-01-04

Datahike features and specs

  • Persistence
    Datahike is a persistent database, which means that it retains data across sessions and can be relied upon for storage that survives application restarts.
  • Datalog queries
    Datahike supports Datalog queries, a powerful and expressive query language that is similar to Prolog, allowing for complex querying of data relationships.
  • Schema flexibility
    Datahike provides schema flexibility that allows developers to define and evolve their data models without needing to perform migrations. This can significantly speed up development.
  • Immutable data structures
    By utilizing immutable data structures, Datahike allows safe concurrent reads and writes, reducing the risk of data corruption and improving application stability.
  • Transactional support
    Datahike offers ACID-compliant transactions, ensuring data integrity and consistent state even in the face of concurrent operations.
  • Integration with Datomic API
    Datahike is designed to be compatible with the Datomic API, making it easier for developers familiar with Datomic to transition and leverage their knowledge.
  • Off-the-shelf scalability
    The architecture of Datahike is conducive to scaling horizontally, providing flexibility to handle growing amounts of data and user load.

Possible disadvantages of Datahike

  • Relatively new ecosystem
    Being a lesser-known and newer alternative compared to databases like Datomic, Datahike may have a smaller community and fewer resources like documentation and third-party integrations.
  • Performance limitations
    While Datahike is designed to be lightweight and flexible, it may not match the performance of more mature databases, especially in very high-load or high-volume scenarios.
  • Limited features
    Datahike may lack some advanced features present in other databases, such as sophisticated indexing or native support for certain types of analytics, which could be necessary for specific applications.
  • Java Virtual Machine (JVM) requirement
    As it runs on the JVM, Datahike requires a Java runtime environment, which might not be ideal or convenient for projects seeking to minimize dependencies or employ lightweight deployment strategies.

Cloud Functions for Firebase features and specs

  • Scalability
    Cloud Functions for Firebase automatically scales up the underlying resources to handle incoming requests and scales down when not in use, allowing developers to handle variable loads efficiently.
  • Integration
    Cloud Functions integrate seamlessly with other Firebase and Google Cloud products, enabling easy event-driven development and streamlined workflow across different services.
  • Reduced Server Management
    As a serverless solution, Cloud Functions reduces the need for manual server management, updates, and maintenance, allowing developers to focus more on writing code.
  • Cost Efficiency
    With a pay-as-you-go pricing model, developers are charged based on the number of function invocations and the resources consumed, making it a cost-efficient solution for many projects.
  • Security
    Cloud Functions benefit from Google Cloud's robust security infrastructure, including automatic updates and integration with Firebase Authentication for secure user management.

Possible disadvantages of Cloud Functions for Firebase

  • Cold Starts
    Cloud Functions can experience latency due to cold starts, which occur when a function is triggered after not being invoked for a certain period, potentially delaying response time for end users.
  • Execution Time Limits
    There are maximum execution time limits for how long a function can run, which may require complex processing tasks to be broken down or handled differently.
  • Limited Languages Support
    Cloud Functions for Firebase support limited programming languages such as JavaScript, Python, and Go, which could be restrictive for developers using different technology stacks.
  • Complexity in Debugging
    Debugging serverless functions can be more complex compared to traditional server-based applications, as it often lacks straightforward access to server logs and requires additional tooling.
  • Vendor Lock-in
    Relying heavily on Firebase may create vendor lock-in, making it more challenging to migrate to other platforms or solutions in the future without significant refactoring.

Category Popularity

0-100% (relative to Datahike and Cloud Functions for Firebase)
Databases
100 100%
0% 0
Developer Tools
0 0%
100% 100
Relational Databases
100 100%
0% 0
Backend As A Service
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Cloud Functions for Firebase should be more popular than Datahike. It has been mentiond 28 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.

Datahike mentions (4)

  • The Ten Rules of Schema Growth
    Datahike [0] provides similar functionality to datomic and is open source. It lacks some features however that Datomic does have [1]. [0]: https://github.com/replikativ/datahike. - Source: Hacker News / over 1 year ago
  • Is Datomic right for my use case?
    You can also consider other durable Datalog options like datahike or datalevin which can work either as lib (SQLite style) or in a client-server setup; if you want to play with bi-temporality XTDB is a rock solid option with very good support and documentation. Source: almost 2 years ago
  • Max Datom: Interactive Datomic Tutorial
    Oh really interesting. I didn't know about that. I was actually going threw the old Mendat code base and was considering using that. I would really like a pure Rust version of Datomic for embed use cases. There is all also Datahike, that is going in that direction too. It is maintained and actively developed. https://github.com/replikativ/datahike. - Source: Hacker News / about 3 years ago
  • Show HN: Matrix-CRDT – real-time collaborative apps using Matrix as backend
    Having an Datomic like store backed by something like this. https://github.com/replikativ/datahike Is an Open Source variant of Datomic. Lambdaforge wants to eventually have this work with CRDTs. Using the Matrix ecosystem for this is quite interesting as it solves many problems for you already. - Source: Hacker News / over 3 years ago

Cloud Functions for Firebase mentions (28)

  • Integrating Zipy and Firebase: A Comprehensive Guide to Enhanced Debugging and App Performance…
    Cloud Functions allow developers to run server-side code without managing servers. These are triggered by Firebase events or HTTP requests and are highly scalable. Use cases include:. - Source: dev.to / 3 months ago
  • I just realized how expensive Firebase is for Social Media Apps
    I tried to make a reddit like app. I used both realtime-database and firestore as database. The billing of the two is different from each other. I used realtime-database for frequently updated data (like or upvote, downvote count for ex.) and firestore for more stable and large data (post, comment, community and user data..). While doing this, I only used database rules, I did not use Cloud functions. So, I... Source: almost 2 years ago
  • Setting up an auto-email micro function for Firebase RTDB
    Const functions = require("firebase-functions"); // // Create and deploy your first functions // // https://firebase.google.com/docs/functions/get-started // // exports.helloWorld = functions.https.onRequest((request, response) => { // functions.logger.info("Hello logs!", {structuredData: true}); // response.send("Hello from Firebase!"); // });. - Source: dev.to / almost 2 years ago
  • Moving my Android app to Google cloud
    Cloud Functions for Firebase - Pros: Aligns to my app which uses Firebase; Cons: have to use Typescript which I have no experience with. Source: about 2 years ago
  • Is it safe to assume the user won't be able to manually call my Firebase functions from the frontend?
    Cloud Functions run on Google's servers and are part of your project, so only you and your project collaborators can deploy that code. Source: over 2 years ago
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What are some alternatives?

When comparing Datahike and Cloud Functions for Firebase, you can also consider the following products

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

Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.

Oracle TimesTen - TimesTen is an in-memory, relational database management system with persistence and...

AWS Lambda - Automatic, event-driven compute service

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

Google Cloud Functions - A serverless platform for building event-based microservices.