JanusGraph

Website

janusgraph.org

Pricing URL

-

$ Details

Categories

#Graph Databases #Databases #NoSQL Databases #Big Data

Datomic

Website

datomic.com

Pricing URL

Official Datomic Pricing

$ Details

-

Categories

#Databases #Relational Databases #NoSQL Databases #Network & Admin

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.

Datomic features and specs

• Immutability
  Datomic employs an append-only data model where data is never overwritten but instead appended, ensuring historical data is always available and providing strong consistency.
• Time Travel Queries
  Datomic allows you to query the database as of any point in time, facilitating auditing and debugging by allowing easy access to historical data states.
• Rich Data Model
  Supports complex data types like maps and sets directly within its schema, providing a flexible way to represent data.
• ACID Transactions
  Datomic supports fully ACID-compliant transactions, ensuring reliable and predictable database operations.
• Scalability
  Separates storage and compute, allowing for horizontal scaling of read operations, making it suitable for handling large datasets.
• Query Flexibility
  Offers a powerful query language that supports recursive queries, making it suitable for complex data retrieval needs.

Possible disadvantages of Datomic

• Complexity
  The architecture of Datomic can be complex to understand and implement, particularly for teams unfamiliar with its design principles.
• Cost
  Can be expensive to operate, especially in a cloud environment, where costs increase with the amount of data stored and the compute resources required.
• Limited Write Throughput
  Due to its append-only design, Datomic can have limited write throughput, which may not be suitable for applications with heavy write requirements.
• Closed Source
  Datomic is a proprietary database system, which may not appeal to organizations that prefer open-source solutions.
• Learning Curve
  Requires a learning curve as its conceptual model and query language are different from traditional databases, potentially requiring additional training.
• Dependency on AWS
  Relying on AWS ecosystem for the storage backend can limit choices for deployment environments, impacting flexibility.

Ted Wilmes on the state of JanusGraph 2018

More videos:

KotlinConf 2018 - Datomic: The Most Innovative DB You've Never Heard Of by August Lilleaas

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