Software Alternatives, Accelerators & Startups

Dgraph VS Cayley

Compare Dgraph VS Cayley and see what are their differences

Dgraph logo Dgraph

A fast, distributed graph database with ACID transactions.

Cayley logo Cayley

Open-source graph database.
  • Dgraph Landing page
    Landing page //
    2023-05-02
  • Cayley Landing page
    Landing page //
    2022-02-03

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.

Cayley features and specs

  • Open Source
    Cayley is open source, which means it is free to use and the source code is available for modification. This promotes transparency and community-driven development.
  • Graph Database
    Cayley is designed as a graph database and is optimized for storing and querying graph-structured data, which can be more efficient for certain types of complex queries.
  • Supports Multiple Storage Backends
    Cayley can be configured to use various storage backends like levelDB, BoltDB, and MongoDB, providing flexibility in terms of storage solutions.
  • Rich Query Language
    Cayley offers a powerful query language inspired by Google's GQL and supports multiple query methods, making it versatile for different query needs.

Possible disadvantages of Cayley

  • Limited Community Support
    As Cayley is an open-source project, it may have limited community support and a smaller ecosystem compared to more established databases like Neo4j.
  • Performance Concerns
    Depending on the size of the data set and the complexity of queries, performance might not match more specialized solutions without careful tuning.
  • Documentation
    The documentation for Cayley may not be as comprehensive or user-friendly as that of more mature projects, which could create challenges for new users.
  • Feature Set
    While Cayley is flexible, it might lack some advanced features present in other graph databases, which could limit its utility for complex use cases.

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)

Cayley videos

Foundry Cigar- Cayley Review

Category Popularity

0-100% (relative to Dgraph and Cayley)
Graph Databases
54 54%
46% 46
Databases
51 51%
49% 49
Developer Tools
100 100%
0% 0
NoSQL Databases
32 32%
68% 68

User comments

Share your experience with using Dgraph and Cayley. 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 seems to be more popular. 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.

Dgraph mentions (21)

  • List of 45 databases in the world
    Dgraphโ€Šโ€”โ€ŠDistributed, fast graph database. - Source: dev.to / about 2 years 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 2 years ago
  • Getting Started with Serverless Edge - Exploring the Options
    DGraph โ€“ A distributed GraphQL database with a graph backend. - Source: dev.to / over 3 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 3 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 3 years ago
View more

Cayley mentions (0)

We have not tracked any mentions of Cayley yet. Tracking of Cayley recommendations started around Mar 2021.

What are some alternatives?

When comparing Dgraph and Cayley, 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.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

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

OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.

Supabase - An open source Firebase alternative

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.