Neo4j vs Tinkerpop

Overview

Neo4j

Stacks1.2K

Followers1.4K

Votes351

GitHub Stars15.3K

Forks2.5K

Tinkerpop

Stacks1

Followers7

Votes0

Neo4j vs Tinkerpop: What are the differences?

Introduction

This article provides a comparison between Neo4j and TinkerPop, two popular graph database technologies, highlighting their key differences.

Query Language: Neo4j uses a native query language called Cypher, specifically designed for querying and manipulating graph data. On the other hand, TinkerPop is not tied to a specific query language and supports multiple query languages, including Gremlin, a graph traversal language.
Architecture: Neo4j follows a native graph storage approach, where the graph data is stored directly in a native graph format. In contrast, TinkerPop follows the Blueprints architecture, which provides a standard API layer on top of different graph databases, allowing for better portability across multiple graph database implementations.
Scalability: Neo4j is known for its strong scalability, with support for horizontal scaling through clustering. It provides a high-performance, distributed graph database solution suitable for handling large datasets efficiently. TinkerPop, being an API layer, relies on the underlying graph database's scalability capabilities and does not provide its own built-in distributed clustering features.
Community and Ecosystem: Neo4j has established a strong community and a rich ecosystem, with a wide range of plugins, libraries, and tools available to enhance its functionalities. It has been around for a longer time and has gained significant popularity. TinkerPop, being an open-standard graph computing framework, has its own growing community and ecosystem but is relatively newer and may have fewer options compared to Neo4j.
Integration and Interoperability: Neo4j supports seamless integration with various programming languages and frameworks, providing dedicated drivers and libraries for languages like Java, Python, and JavaScript. TinkerPop, being an API layer, offers a standardized way to interact with graph databases, enabling interoperability across multiple databases that adhere to the TinkerPop standards.
Graph Processing Capabilities: Neo4j provides a rich set of built-in graph processing capabilities, such as graph algorithms and advanced query optimization techniques. TinkerPop, being a generic graph computing framework, focuses more on providing a standardized API for interaction and traversing graphs, rather than specialized graph processing functionalities.

In summary, Neo4j and TinkerPop differ in terms of their query languages, architecture, scalability, community support, interoperability, and graph processing capabilities. Neo4j provides a native graph database solution with a dedicated query language and stronger scalability features, while TinkerPop offers a more flexible, standardized API layer with support for multiple databases.

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CLI (Node.js)

Manual

Detailed Comparison

Neo4j	Tinkerpop
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.	Home page of The Apache Software Foundation
intuitive, using a graph model for data representation;reliable, with full ACID transactions;durable and fast, using a custom disk-based, native storage engine;massively scalable, up to several billion nodes/relationships/properties;highly-available, when distributed across multiple machines;expressive, with a powerful, human readable graph query language;fast, with a powerful traversal framework for high-speed graph queries;embeddable, with a few small jars;simple, accessible by a convenient REST interface or an object-oriented Java API	-
Statistics
GitHub Stars 15.3K	GitHub Stars -
GitHub Forks 2.5K	GitHub Forks -
Stacks 1.2K	Stacks 1
Followers 1.4K	Followers 7
Votes 351	Votes 0
Pros & Cons
Pros 69 Cypher – graph query language 61 Great graphdb 33 Open source 31 Rest api 27 High-Performance Native API Cons 9 Comparably slow 4 Can't store a vertex as JSON 1 Doesn't have a managed cloud service at low cost	No community feedback yet

What are some alternatives to Neo4j, Tinkerpop?

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.

JanusGraph

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.

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

Neo4j vs Tinkerpop: What are the differences?

Introduction

This article provides a comparison between Neo4j and TinkerPop, two popular graph database technologies, highlighting their key differences.

Query Language: Neo4j uses a native query language called Cypher, specifically designed for querying and manipulating graph data. On the other hand, TinkerPop is not tied to a specific query language and supports multiple query languages, including Gremlin, a graph traversal language.
Architecture: Neo4j follows a native graph storage approach, where the graph data is stored directly in a native graph format. In contrast, TinkerPop follows the Blueprints architecture, which provides a standard API layer on top of different graph databases, allowing for better portability across multiple graph database implementations.
Scalability: Neo4j is known for its strong scalability, with support for horizontal scaling through clustering. It provides a high-performance, distributed graph database solution suitable for handling large datasets efficiently. TinkerPop, being an API layer, relies on the underlying graph database's scalability capabilities and does not provide its own built-in distributed clustering features.
Community and Ecosystem: Neo4j has established a strong community and a rich ecosystem, with a wide range of plugins, libraries, and tools available to enhance its functionalities. It has been around for a longer time and has gained significant popularity. TinkerPop, being an open-standard graph computing framework, has its own growing community and ecosystem but is relatively newer and may have fewer options compared to Neo4j.
Integration and Interoperability: Neo4j supports seamless integration with various programming languages and frameworks, providing dedicated drivers and libraries for languages like Java, Python, and JavaScript. TinkerPop, being an API layer, offers a standardized way to interact with graph databases, enabling interoperability across multiple databases that adhere to the TinkerPop standards.
Graph Processing Capabilities: Neo4j provides a rich set of built-in graph processing capabilities, such as graph algorithms and advanced query optimization techniques. TinkerPop, being a generic graph computing framework, focuses more on providing a standardized API for interaction and traversing graphs, rather than specialized graph processing functionalities.

Neo4j vs Tinkerpop

Overview

Neo4j vs Tinkerpop: What are the differences?