Dgraph

Website

dgraph.io

Pricing URL

Official Dgraph Pricing

$ Details

Categories

#Graph Databases #Databases #NoSQL Databases #Big Data

JanusGraph

Website

janusgraph.org

Pricing URL

-

$ Details

Categories

#Graph Databases #Databases #NoSQL Databases #Big Data

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.

JanusGraph features and specs

• Scalability
  JanusGraph is designed to support large-scale graph data processing, allowing it to handle huge graphs distributed across multiple machines effectively.
• Compatibility
  It is compatible with various storage backends (like HBase, Apache Cassandra, and Google Bigtable) and indexing backends (such as Elasticsearch and Solr), providing flexibility in integration.
• APIs and Queries
  JanusGraph supports the TinkerPop stack, enabling developers to use powerful graph traversal language Gremlin for query operations.
• Open Source
  Being open-source, JanusGraph benefits from community contributions and offers transparency and extensibility to users.
• Transaction Support
  It provides ACID transactions, ensuring reliability and consistency in graph operations.

Possible disadvantages of JanusGraph

• Complexity
  The configuration and optimization of JanusGraph can be complex due to its support for multiple backends and the various configurations required for different setups.
• Performance Variability
  Performance can vary significantly depending on the chosen backend datastore and its configuration, requiring careful consideration and tuning.
• Operational Overhead
  Managing the infrastructure, especially when using distributed storage solutions, can introduce significant operational overhead.
• Community and Support
  While it is open source, the community is not as vast or active as some other database technologies, which may limit available support and resources.
• Resource Intensity
  Running JanusGraph with large datasets and multiple distributed nodes can require substantial resources, both in terms of hardware and maintenance.

Intro to Slash GraphQL from Dgraph

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Ted Wilmes on the state of JanusGraph 2018

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