Software Alternatives, Accelerators & Startups

Apache TinkerPop VS Dgraph

Compare Apache TinkerPop VS Dgraph and see what are their differences

Apache TinkerPop logo Apache TinkerPop

Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP).

Dgraph logo Dgraph

A fast, distributed graph database with ACID transactions.
  • Apache TinkerPop Landing page
    Landing page //
    2022-01-24
  • Dgraph Landing page
    Landing page //
    2023-05-02

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.

Dgraph features and specs

  • High Performance
    Dgraph is optimized for high-throughput and low-latency scenarios, making it suitable for real-time applications with large datasets.
  • Horizontal Scalability
    Dgraph offers seamless horizontal scalability, allowing the system to expand across multiple nodes to handle increased workloads.
  • GraphQL Compatibility
    Dgraph provides native support for GraphQL, allowing developers to use a widely accepted query language with their graph database.
  • Distributed Architecture
    Being a distributed graph database, Dgraph ensures data replication and high availability across different geographical locations.
  • Strong Consistency
    Dgraph offers strong consistency guarantees, ensuring that all nodes see the same data at the same time, which is crucial for many applications.

Possible disadvantages of Dgraph

  • Complex Setup
    Setting up and managing Dgraph can be complex, especially for users not familiar with distributed systems.
  • Resource Intensive
    Running Dgraph in a production environment can be resource-intensive, requiring significant computational resources and memory.
  • Learning Curve
    For developers new to graph databases, there may be a steep learning curve compared to more traditional relational databases.
  • Limited Tooling Ecosystem
    Compared to some older graph databases, Dgraph's ecosystem, in terms of third-party tools and integrations, is not as mature.
  • Community Support
    As a relatively newer entrant in the database market, Dgraph may have less community-driven support compared to more established databases.

Apache TinkerPop videos

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

Add video

Dgraph videos

Intro to Slash GraphQL from Dgraph

More videos:

  • Review - Getting started with Dgraph #5: Tweet graph, string indices, and keyword-based searching
  • Review - Graph Database: Intro to Dgraph's Query Language (2017)

Category Popularity

0-100% (relative to Apache TinkerPop and Dgraph)
NoSQL Databases
60 60%
40% 40
Graph Databases
40 40%
60% 60
Databases
41 41%
59% 59
Developer Tools
0 0%
100% 100

User comments

Share your experience with using Apache TinkerPop and Dgraph. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Dgraph should be more popular than Apache TinkerPop. It has been mentiond 21 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.

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 / about 2 months 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 / over 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

Dgraph mentions (21)

  • List of 45 databases in the world
    Dgraph — Distributed, fast graph database. - Source: dev.to / 11 months ago
  • How to choose the right type of database
    Dgraph: A distributed and scalable graph database known for high performance. It's a good fit for large-scale graph processing, offering a GraphQL-like query language and gRPC API support. - Source: dev.to / over 1 year ago
  • Getting Started with Serverless Edge - Exploring the Options
    DGraph – A distributed GraphQL database with a graph backend. - Source: dev.to / over 2 years ago
  • Fluree DB - A datomic like database that I just discovered
    How does it compare to, say grakn (renamed https://vaticle.com/, I think?), or draph (https://dgraph.io/), or Ontotext's GraphDB (https://www.ontotext.com/products/graphdb/), or Datomic? Source: over 2 years ago
  • GKE with Consul Service Mesh
    Consul Connect service mesh has a higher memory footprint, so on a small cluster with e5-medium nodes (2 vCPUs, 4 GB memory), you will only be able to support a maximum of 6 side-car proxies. In order to get an application like Dgraph working, which will have 6 nodes (3 Dgraph Alpha pods and 3 Dgraph Zero pods) for high availability along with at least one client, a larger footprint with more robust Kubernetes... - Source: dev.to / over 2 years ago
View more

What are some alternatives?

When comparing Apache TinkerPop and Dgraph, you can also consider the following products

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

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

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

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.

NetworkX - NetworkX is a Python language software package for the creation, manipulation, and study of the...

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