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Hasura VS Datahike

Compare Hasura VS Datahike and see what are their differences

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Hasura logo Hasura

Hasura is an open platform to build scalable app backends, offering a built-in database, search, user-management and more.

Datahike logo Datahike

A durable datalog database adaptable for distribution.
  • Hasura Landing page
    Landing page //
    2023-10-21
  • Datahike Landing page
    Landing page //
    2023-08-22

Hasura features and specs

  • Real-Time Data
    Hasura provides built-in support for GraphQL subscriptions, allowing you to easily implement real-time data updates in your applications.
  • Auto-Generated APIs
    With Hasura, you can instantly generate a fully-functional, scalable GraphQL API from your existing databases without writing any code.
  • Authorization and Authentication
    Hasura provides granular authorization controls and integrates well with various authentication services, helping to secure your data access.
  • Microservices & Event Triggers
    Hasura allows you to create event-driven architectures by allowing you to trigger webhooks based on specified database events.
  • Scalability
    Designed for performance, Hasura can handle large-scale applications by optimizing database queries and offering load-balancing capabilities.
  • Multi-Data Source Support
    Hasura can connect to multiple data sources and databases, making it a versatile choice for complex architectures.
  • Developer Productivity
    The tool significantly reduces the time required for backend development, allowing developers to focus on building frontend features and improving user experience.
  • Community and Support
    Hasura has a growing community and offers comprehensive documentation, which can be invaluable for troubleshooting and getting the most out of the platform.

Possible disadvantages of Hasura

  • Complex Initial Setup
    Although Hasura simplifies many tasks, setting it up initially can be complex and may require a good understanding of both GraphQL and your underlying database.
  • Vendor Lock-In Concerns
    Depending heavily on Hasura can create vendor lock-in situations, making it difficult to switch technologies later without significant redevelopment effort.
  • Learning Curve
    Developers unfamiliar with GraphQL, event-driven architectures, or advanced database concepts may face a steep learning curve when adopting Hasura.
  • Limited Customization
    Some advanced use cases may require lower-level customizations not easily achievable through Hasura’s auto-generated APIs.
  • Performance Overhead
    Although optimized for performance, the additional layer Hasura introduces can still introduce latency, especially in highly complex queries.
  • Debugging Complexity
    Diagnosing issues can sometimes be complicated due to the number of components involved, including the database, Hasura, and the generated APIs.
  • Cost
    While Hasura offers a free tier, advanced features and enterprise-level support come at a cost, which can add up as your project scales.

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.

Hasura videos

+ Add

Scott Tries Hasura - A Realtime GraphQL API Builder

More videos:

  • Review - Evaluating Hasura
  • Review - The founder of Hasura teaching me about Hasura - FUN!

Datahike videos

No Datahike videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Hasura and Datahike)

Hasura

Datahike

GraphQL
100 100%
GraphQL
0% 0
Databases
0 0%
Databases
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Relational Databases
0 0%
Relational Databases
100% 100

User comments

Share your experience with using Hasura and Datahike. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Hasura seems to be a lot more popular than Datahike. While we know about 123 links to Hasura, we've tracked only 4 mentions of Datahike. 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.

Hasura mentions (123)

  • Boring on Purpose: Bold Moves in Internal Tooling
    A few years back, I decided to replace our spreadsheet-based host and service registries with a proper, Web-based asset registry. It took us a few days to hack together a simple system that we could use to track our infrastructure elements. It was not a big project -- just a simple app backed by a database, Hasura, and a React frontend. Since we were already using OpenID for authentication, it was easy for our... - Source: dev.to / 9 days ago
  • Supabase Alternatives 🔄 in 2025 😼
    Hasura is a neck-to-neck competitor to Supabase as a BaaS, but with a crucial difference: its GraphQL-first approach. Unlike Supabase, Hasura doesn't bundle database services, allowing it to work with virtually any database including Supabase's own Postgres, Neon, and others. - Source: dev.to / 3 months ago
  • Automatically Generate REST and GraphQL APIs From Your Database
    Hasura and PostGraphile lead the PostgreSQL GraphQL landscape. Hasura provides real-time subscriptions and a powerful permissions system, while PostGraphile offers deep PostgreSQL integration and excellent performance for complex queries. - Source: dev.to / 6 months ago
  • The Myth of GraphQL
    Here is an example data schema we get for a query using Hasura and GraphQL-Codegen. - Source: dev.to / 8 months ago
  • Hasura CLI on NixOS: A Working Solution
    Hasura is a great tool. I was worried about a few things such as huge RAM consumption, excessive focus on new features and functions despite many outstanding issues, long time rewrite of the server in Rust, etc... - Source: dev.to / 10 months ago
View more

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

What are some alternatives?

When comparing Hasura and Datahike, you can also consider the following products

Supabase - An open source Firebase alternative

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

GraphQl Editor - Editor for GraphQL that lets you draw GraphQL schemas using visual nodes

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

Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.

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

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