Software Alternatives, Accelerators & Startups

Datahike VS Apache TinkerPop

Compare Datahike VS Apache TinkerPop and see what are their differences

Datahike logo Datahike

A durable datalog database adaptable for distribution.

Apache TinkerPop logo Apache TinkerPop

Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP).
  • Datahike Landing page
    Landing page //
    2023-08-22
  • Apache TinkerPop Landing page
    Landing page //
    2022-01-24

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.

Apache TinkerPop features and specs

  • Graph Abstraction
    Apache TinkerPop provides a generalized graph computing framework, allowing developers to work with a property graph model that supports both OLTP and OLAP use cases.
  • Gremlin Query Language
    Gremlin is a powerful and flexible graph traversal language that supports both imperative and declarative query styles, making it versatile for complex graph queries.
  • Vendor Neutrality
    TinkerPop is vendor-agnostic and supports multiple graph database systems such as Neo4j, JanusGraph, and Amazon Neptune, providing flexibility in choosing underlying storage.
  • Rich Ecosystem
    TinkerPop has a strong ecosystem with numerous integrations, plugins, and extensions, which helps in building applications more efficiently.
  • Community and Support
    Being part of the Apache Software Foundation, TinkerPop benefits from a strong community, extensive documentation, and regular updates.

Possible disadvantages of Apache TinkerPop

  • Complexity
    The flexibility and power of TinkerPop come with a steep learning curve, especially for those new to graph databases or the Gremlin language.
  • Performance Overhead
    Due to its abstraction layer, there might be performance overhead compared to using a graph database's native query language directly.
  • Limited Graph Algorithms
    Compared to specialized graph processing frameworks like Apache Giraph or GraphX, TinkerPop might have limitations in built-in graph algorithms.
  • Integration Overhead
    Integrating TinkerPop with existing systems may require additional overhead in terms of setup and configuration, especially if leveraging its multi-database support.

Category Popularity

0-100% (relative to Datahike and Apache TinkerPop)
Databases
70 70%
30% 30
NoSQL Databases
48 48%
52% 52
Relational Databases
100 100%
0% 0
Graph Databases
0 0%
100% 100

User comments

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Social recommendations and mentions

Apache TinkerPop might be a bit more popular than Datahike. We know about 5 links to it since March 2021 and only 4 links to 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.

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

Apache TinkerPop mentions (5)

  • All About Graph RAG
    Part of the Apache TinkerPop framework, an imperative graph traversal language for the property graph model. - Source: dev.to / 15 days ago
  • Setup Azure Cosmos DB for Gremlin in Spring Boot Java
    The API for Gremlin is built based on Apache TinkerPop, a graph computing framework that uses the Gremlin query language. - Source: dev.to / about 1 year ago
  • Testcontainers
    You might take a look at Tinkerpop: https://tinkerpop.apache.org/. - Source: Hacker News / about 1 year ago
  • Getting Started with Redis and RedisGraph
    Property Graph, mainly represented as node and relationship in which they can have properties. The database for this kind of data is usually called Graph Database. Gremlin - by TinkerPop project and Cypher - by Neo4J are their query language (also AQL - Arango Query Language - by ArangoDB, but AQL does not only provides graph query language). - Source: dev.to / over 3 years ago
  • Should You Invent a New Query Language? (Probably Not)
    The most common graph query language at the moment would be Gremlin, which is part of the Apache TinkePop graph computing framework. It is simple to write, easy to learn, and widely supported by many graph databases and even non-graph databases that can emulate graph queries. On the other hand, it can be verbose for long queries but generally works well for both OLTP and analysis work. - Source: dev.to / almost 4 years ago

What are some alternatives?

When comparing Datahike and Apache TinkerPop, 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

Ontotext Graph DB - Graph DB is a semantic graph database that serves organizations to store, organize and manage content.