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AllegroGraph VS RedisGraph

Compare AllegroGraph VS RedisGraph and see what are their differences

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Contents:
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AllegroGraph logo AllegroGraph

AllegroGraph is a high-performance, persistent graph database.

RedisGraph logo RedisGraph

A high-performance graph database implemented as a Redis module.
  • AllegroGraph Landing page
    Landing page //
    2018-11-12
  • RedisGraph Landing page
    Landing page //
    2023-03-24

AllegroGraph features and specs

  • Scalability
    AllegroGraph is designed to handle large-scale graphs, making it suitable for big data applications and enterprises needing to process extensive interconnected data.
  • Standards Compliance
    The database supports RDF, SPARQL, and other W3C standards, ensuring compatibility and interoperability with other semantic web technologies.
  • Performance
    Optimized for high performance, AllegroGraph provides efficient querying and data processing capabilities, even with complex and large datasets.
  • Geospatial and Temporal Reasoning
    It offers advanced features for geospatial and temporal reasoning, enabling complex analytics involving geographic data and time-based patterns.
  • Advanced Analytics
    It supports various advanced analytics functionalities, including machine learning integration for AI-driven insights and pattern recognition.

Possible disadvantages of AllegroGraph

  • Cost
    AllegroGraph is a commercial product, and licensing costs can be significant, potentially limiting accessibility for smaller organizations and projects with constrained budgets.
  • Complexity
    The advanced features and flexibility come with complexity, which may require a steep learning curve for new users or developers unfamiliar with semantic graph databases.
  • Resource Intensive
    Running AllegroGraph efficiently may require significant computational resources, such as memory and processing power, which can increase infrastructure costs.
  • Limited Adoption
    Although powerful, AllegroGraph's adoption may be lower than some mainstream graph databases, potentially leading to limited community support and third-party integrations.
  • Proprietary Technology
    Being a proprietary solution, AllegroGraph may lack the flexibility or customizability some open-source alternatives offer, potentially leading to vendor lock-in concerns.

RedisGraph features and specs

  • High Performance
    RedisGraph is designed for fast operations using an in-memory structure with optimized algorithms. It leverages sparse matrices and linear algebra to perform graph operations efficiently, resulting in high query performance suitable for real-time applications.
  • Cypher Query Language
    RedisGraph uses the Cypher query language, which is intuitive and widely used. This makes it easier for those familiar with graph databases to write queries without a steep learning curve.
  • Integration with Redis Ecosystem
    Being part of the Redis ecosystem allows RedisGraph to integrate seamlessly with other Redis modules and core features, benefiting from Redis's scalability, replication, and persistence capabilities.
  • Open Source and Active Community
    As an open-source project, RedisGraph benefits from community contributions and transparency. The active development and support community can be advantageous for users seeking collaboration or needing assistance.

Possible disadvantages of RedisGraph

  • Memory Usage
    RedisGraph operates in-memory, which can lead to high memory usage, especially for large datasets. This can make it impractical for very large graphs without sufficient hardware resources.
  • Limited Graph Features
    Compared to some specialized graph databases, RedisGraph may offer a more limited set of advanced graph-specific features. This could be a constraint for users needing specific functionalities like multi-tenancy or advanced analytical capabilities.
  • Persistence Limitations
    While RedisGraph benefits from Redis’s persistence mechanisms, it primarily functions as an in-memory database. Thus, ensuring durability and handling large datasets with persistence needs might require additional configuration and resources.
  • Complexity for Beginners
    Though Cypher is relatively easy to learn, those new to graph databases might find the concepts and setup of RedisGraph complex, especially if they need to install and manage Redis modules and configurations.

AllegroGraph videos

+ Add

Knowledge Graph Technology Showcase Honest Review: AllegroGraph (Winter 2023 E6)

More videos:

  • Tutorial - Hosted Allegrograph Tutorial
  • Demo - AllegroGraph Where 2.0 demo

RedisGraph videos

+ Add

Deep Dive into RedisGraph

More videos:

  • Review - Creating a Model of Human Physiology w/RedisGraph - RedisConf 2020

Category Popularity

0-100% (relative to AllegroGraph and RedisGraph)

AllegroGraph

RedisGraph

Graph Databases
31 31%
Graph Databases
69% 69
Databases
29 29%
Databases
71% 71
NoSQL Databases
31 31%
NoSQL Databases
69% 69
Big Data
41 41%
Big Data
59% 59

User comments

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Social recommendations and mentions

Based on our record, RedisGraph should be more popular than AllegroGraph. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AllegroGraph mentions (1)

  • Does any useful knowledge graph tool that you recommend？
    However, Protege is a modeling tool not a database. So when you start getting into large amounts of data (e.g., 10K instances or more) you will need another tool, ideally a database. There are tools to do what's called Data Virtualization, where you can represent your data (what OWL users call the A-Box, i.e., the equivalent of instances in OOP or rows in a relational DB) in a relational database and map the data... Source: over 2 years ago

RedisGraph mentions (2)

What are some alternatives?

When comparing AllegroGraph and RedisGraph, you can also consider the following products

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

JanusGraph - JanusGraph is a scalable graph database optimized for storing and querying graphs.

NetworkX - NetworkX is a Python language software package for the creation, manipulation, and study of the...

Apache TinkerPop - Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP).

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