JanusGraph vs TerminusDB

Overview

JanusGraph

Stacks43

Followers96

Votes0

TerminusDB

Stacks6

Followers18

Votes0

JanusGraph vs TerminusDB: What are the differences?

Introduction: In the realm of database management systems, JanusGraph and TerminusDB are two distinct platforms that cater to different use cases and requirements. Below are some key differences that set these systems apart.

Data Model: JanusGraph utilizes a property graph data model that emphasizes relationships between entities, making it well-suited for graph-based applications. On the other hand, TerminusDB employs a schema-driven document data model that facilitates structured data storage and retrieval.
Query Language: JanusGraph supports Apache TinkerPop Gremlin as its query language, which is a versatile graph traversal language suitable for complex graph queries. TerminusDB, in contrast, uses WOQL (Web Object Query Language) designed specifically for querying and manipulating schema-rich data.
Consistency Model: JanusGraph provides eventual consistency, allowing for high availability and fault tolerance in distributed environments. TerminusDB offers ACID (Atomicity, Consistency, Isolation, Durability) compliance, ensuring data integrity and reliability in transaction processing.
Deployment Options: JanusGraph is typically deployed on distributed systems like Apache Hadoop or Apache Cassandra to leverage scaling capabilities for large-scale graph databases. TerminusDB, on the other hand, can be self-hosted or cloud-hosted, providing flexibility in deployment options.
Use Cases: JanusGraph is commonly used for social networking, recommendation systems, and knowledge graphs where complex relationships need to be represented and queried efficiently. TerminusDB, on the other hand, is ideal for data governance, knowledge management, and collaborative projects requiring structured data management.
Community and Ecosystem: JanusGraph has a vibrant open-source community backed by the Apache Software Foundation, providing ongoing support, documentation, and ecosystem development. TerminusDB is supported by a dedicated team focused on data collaboration and governance, offering specialized tools and resources for its users.

In Summary, JanusGraph and TerminusDB differ in their data models, query languages, consistency models, deployment options, use cases, and community ecosystems, catering to diverse needs in the database management landscape.

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CLI (Node.js)

Manual

Detailed Comparison

JanusGraph	TerminusDB
It is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. It is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.	It is a database built for data people. Terminus is a model driven graph database designed specifically for the web-age. The result is unified, well-structured & refined data - the jet fuel of future business. It greatly reduces the time and effort required to build any application that shares, manipulates or edits data.
Elastic and linear scalability for a growing data and user base; Data distribution and replication for performance and fault tolerance; Multi-datacenter high availability and hot backups; Support for ACID and eventual consistency; Support for various storage backends: HBase, Cassandra, Bigtable, DynamoDB, BerkeleyDB; Support for global graph data analytics, reporting, and ETL through integration with big data platforms: Spark, Giraph, Hadoop; Support for geo, numeric range, and full-text search via: ElasticSearch, Solr, Lucene; Native integration with the Apache TinkerPop graph stack; Open source under the Apache 2 license	Make complex data models easy, maintainable and enforced; Overcome the Object Impedance mismatch without turning your Database into an incomprehensible soup; Allow you to search for repeating patterns using recursion; Give you powerful temporal queries using finite domain constraint logic; Enable the sharing of data using linked open data formats RDF and JSON-LD making scientific or organisational information sharing easy; Help you automate the production of UI and data-entry by knowing what data means
Statistics
Stacks 43	Stacks 6
Followers 96	Followers 18
Votes 0	Votes 0
Integrations
Apache Spark Amazon DynamoDB Cassandra Apache Solr ScyllaDB	No integrations available

What are some alternatives to JanusGraph, TerminusDB?

Neo4j

Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.

Dgraph

Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.

RedisGraph

RedisGraph is a graph database developed from scratch on top of Redis, using the new Redis Modules API to extend Redis with new commands and capabilities. Its main features include: - Simple, fast indexing and querying - Data stored in RAM, using memory-efficient custom data structures - On disk persistence - Tabular result sets - Simple and popular graph query language (Cypher) - Data Filtering, Aggregation and ordering

Cayley

Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.

Blazegraph

It is a fully open-source high-performance graph database supporting the RDF data model and RDR. It operates as an embedded database or over a client/server REST API.

Graph Engine

The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set.

FalkorDB

FalkorDB is developing a novel graph database that revolutionizes the graph databases and AI industries. Our graph database is based on novel but proven linear algebra algorithms on sparse matrices that deliver unprecedented performance up to two orders of magnitude greater than the leading graph databases. Our goal is to provide the missing piece in AI in general and LLM in particular, reducing hallucinations and enhancing accuracy and reliability. We accomplish this by providing a fast and interactive knowledge graph, which provides a superior solution to the common solutions today.

Titan

Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.

TypeDB

TypeDB is a database with a rich and logical type system. TypeDB empowers you to solve complex problems, using TypeQL as its query language.

Memgraph

Memgraph is a streaming graph application platform that helps you wrangle your streaming data, build sophisticated models that you can query in real-time, and develop applications you never thought possible in days, not months.

Related Comparisons

JanusGraph vs TerminusDB: What are the differences?

Data Model: JanusGraph utilizes a property graph data model that emphasizes relationships between entities, making it well-suited for graph-based applications. On the other hand, TerminusDB employs a schema-driven document data model that facilitates structured data storage and retrieval.
Query Language: JanusGraph supports Apache TinkerPop Gremlin as its query language, which is a versatile graph traversal language suitable for complex graph queries. TerminusDB, in contrast, uses WOQL (Web Object Query Language) designed specifically for querying and manipulating schema-rich data.
Consistency Model: JanusGraph provides eventual consistency, allowing for high availability and fault tolerance in distributed environments. TerminusDB offers ACID (Atomicity, Consistency, Isolation, Durability) compliance, ensuring data integrity and reliability in transaction processing.
Deployment Options: JanusGraph is typically deployed on distributed systems like Apache Hadoop or Apache Cassandra to leverage scaling capabilities for large-scale graph databases. TerminusDB, on the other hand, can be self-hosted or cloud-hosted, providing flexibility in deployment options.
Use Cases: JanusGraph is commonly used for social networking, recommendation systems, and knowledge graphs where complex relationships need to be represented and queried efficiently. TerminusDB, on the other hand, is ideal for data governance, knowledge management, and collaborative projects requiring structured data management.
Community and Ecosystem: JanusGraph has a vibrant open-source community backed by the Apache Software Foundation, providing ongoing support, documentation, and ecosystem development. TerminusDB is supported by a dedicated team focused on data collaboration and governance, offering specialized tools and resources for its users.

JanusGraph vs TerminusDB

Overview