ArangoDB vs JanusGraph

Overview

ArangoDB

Stacks273

Followers442

Votes192

JanusGraph

Stacks43

Followers96

Votes0

ArangoDB vs JanusGraph: What are the differences?

Data Model: ArangoDB is a multi-model database that supports key/value, document, and graph data models natively, allowing users to mix and match these data models within a single query. In contrast, JanusGraph is a graph database that focuses solely on graph data modeling, making it more specialized for graph-related operations.
Native Graph Processing: ArangoDB provides built-in graph processing capabilities, allowing users to run graph algorithms and traversals directly within the database engine. On the other hand, JanusGraph relies on external graph processing frameworks like Apache Spark or Apache Giraph for advanced graph analytics.
Consistency Models: ArangoDB offers different consistency models such as full, sync, and linearizable to cater to various application requirements. JanusGraph primarily follows the eventual consistency model, which may lead to slightly outdated or conflicting data during network partitions or failures.
Scalability: ArangoDB supports horizontal scalability through cluster configurations, enabling users to distribute data across multiple nodes for high availability and performance. JanusGraph also supports scaling out by utilizing distributed storage backends like Apache Cassandra or HBase for storing graph data.
Deployment Options: ArangoDB can be deployed as a standalone server, a cluster setup, or in a distributed environment based on user needs. JanusGraph, being an open-source project, provides flexibility in deployment options but requires additional setup and configuration for distributed deployments compared to ArangoDB.
Query Language: ArangoDB uses its query language called AQL (ArangoDB Query Language) that supports SQL-like syntax for querying data across different data models. In contrast, JanusGraph follows the Gremlin query language, which is a graph traversal language for querying graph databases.

In Summary, ArangoDB offers multi-model flexibility, built-in graph processing, various consistency models, scalability options, versatile deployment choices, and a unique AQL query language, while JanusGraph specializes in graph data modeling, relies on external graph processing frameworks, follows an eventual consistency model, supports scaling with distributed storage backends, requires specific setup for deployment, and uses the Gremlin query language.

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CLI (Node.js)

Manual

Detailed Comparison

ArangoDB	JanusGraph
A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.	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.
multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb	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
Statistics
Stacks 273	Stacks 43
Followers 442	Followers 96
Votes 192	Votes 0
Pros & Cons
Pros 37 Grahps and documents in one DB 26 Intuitive and rich query language 25 Good documentation 25 Open source 21 Joins for collections Cons 3 Web ui has still room for improvement 2 No support for blueprints standard, using custom AQL	No community feedback yet
Integrations
No integrations available	Apache Spark Amazon DynamoDB Cassandra Apache Solr ScyllaDB

What are some alternatives to ArangoDB, JanusGraph?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

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.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Related Comparisons

ArangoDB vs JanusGraph: What are the differences?

Data Model: ArangoDB is a multi-model database that supports key/value, document, and graph data models natively, allowing users to mix and match these data models within a single query. In contrast, JanusGraph is a graph database that focuses solely on graph data modeling, making it more specialized for graph-related operations.
Native Graph Processing: ArangoDB provides built-in graph processing capabilities, allowing users to run graph algorithms and traversals directly within the database engine. On the other hand, JanusGraph relies on external graph processing frameworks like Apache Spark or Apache Giraph for advanced graph analytics.
Consistency Models: ArangoDB offers different consistency models such as full, sync, and linearizable to cater to various application requirements. JanusGraph primarily follows the eventual consistency model, which may lead to slightly outdated or conflicting data during network partitions or failures.
Scalability: ArangoDB supports horizontal scalability through cluster configurations, enabling users to distribute data across multiple nodes for high availability and performance. JanusGraph also supports scaling out by utilizing distributed storage backends like Apache Cassandra or HBase for storing graph data.
Deployment Options: ArangoDB can be deployed as a standalone server, a cluster setup, or in a distributed environment based on user needs. JanusGraph, being an open-source project, provides flexibility in deployment options but requires additional setup and configuration for distributed deployments compared to ArangoDB.
Query Language: ArangoDB uses its query language called AQL (ArangoDB Query Language) that supports SQL-like syntax for querying data across different data models. In contrast, JanusGraph follows the Gremlin query language, which is a graph traversal language for querying graph databases.

ArangoDB vs JanusGraph

Overview