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Datahike VS Ontotext Graph DB

Compare Datahike VS Ontotext Graph DB and see what are their differences

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Contents:
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Datahike logo Datahike

A durable datalog database adaptable for distribution.

Ontotext Graph DB logo Ontotext Graph DB

Graph DB is a semantic graph database that serves organizations to store, organize and manage content.
  • Datahike Landing page
    Landing page //
    2023-08-22
  • Ontotext Graph DB Landing page
    Landing page //
    2023-10-01

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.

Ontotext Graph DB features and specs

No features have been listed yet.

Category Popularity

0-100% (relative to Datahike and Ontotext Graph DB)

Datahike

Ontotext Graph DB

Databases
77 77%
Databases
23% 23
NoSQL Databases
60 60%
NoSQL Databases
40% 40
Relational Databases
100 100%
Relational Databases
0% 0
Graph Databases
0 0%
Graph Databases
100% 100

User comments

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Social recommendations and mentions

Based on our record, Datahike seems to be more popular. It has been mentiond 4 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

Ontotext Graph DB mentions (0)

We have not tracked any mentions of Ontotext Graph DB yet. Tracking of Ontotext Graph DB recommendations started around Mar 2021.

What are some alternatives?

When comparing Datahike and Ontotext Graph DB, you can also consider the following products

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

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

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

JanusGraph - JanusGraph is a scalable graph database optimized for storing and querying graphs.

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

Amazon Neptune - Amazon Neptune is a fully managed graph database service that works with highly connected datasets. Learn about the benefits and popular use cases.

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