Software Alternatives, Accelerators & Startups

ArangoDB VS Apache Arrow

Compare ArangoDB VS Apache Arrow and see what are their differences

ArangoDB logo ArangoDB

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

Apache Arrow logo Apache Arrow

Apache Arrow is a cross-language development platform for in-memory data.
  • ArangoDB Landing page
    Landing page //
    2023-01-20
  • Apache Arrow Landing page
    Landing page //
    2021-10-03

ArangoDB features and specs

  • Graph DB

Apache Arrow features and specs

  • In-Memory Columnar Format
    Apache Arrow stores data in a columnar format in memory which allows for efficient data processing and analytics by enabling operations on entire columns at a time.
  • Language Agnostic
    Arrow provides libraries in multiple languages such as C++, Java, Python, R, and more, facilitating cross-language development and enabling data interchange between ecosystems.
  • Interoperability
    Arrow's ability to act as a data transfer protocol allows easy interoperability between different systems or applications without the need for serialization or deserialization.
  • Performance
    Designed for high performance, Arrow can handle large data volumes efficiently due to its zero-copy reads and SIMD (Single Instruction, Multiple Data) operations.
  • Ecosystem Integration
    Arrow integrates well with various data processing systems like Apache Spark, Pandas, and more, making it a versatile choice for data applications.

Possible disadvantages of Apache Arrow

  • Complexity
    The use of Apache Arrow can introduce additional complexity, especially for smaller projects or those which do not require high-performance data interchange.
  • Learning Curve
    Getting accustomed to Apache Arrow can take time due to its unique in-memory format and APIs, especially for developers who are new to columnar data processing.
  • Memory Usage
    While Arrow excels in speed and performance, the memory consumption can be higher compared to row-based storage formats, potentially becoming a bottleneck.
  • Maturity
    Although rapidly evolving, some Arrow components or language implementations may not be as mature or feature-complete, potentially leading to limitations in certain use cases.
  • Integration Challenges
    While Arrow aims for broad compatibility, integrating it into existing systems may require substantial effort, affecting development timelines.

Analysis of ArangoDB

Overall verdict

  • ArangoDB is indeed a good option for those looking for a flexible, feature-rich, and scalable database solution. It caters to modern applications requiring diverse data representations and complex querying capabilities, particularly when graph functionality is vital. However, the right choice depends on specific project requirements and familiarity with ArangoDB’s features and ecosystem.

Why this product is good

  • ArangoDB is a highly versatile database solution known for its multi-model approach, which supports document, key/value, and graph data models. This flexibility allows for complex data structures and enables developers to use the most suitable model for their specific application needs all within a single database. Additionally, ArangoDB offers robust features such as a powerful query language (AQL), scalability, a flexible architecture, and native support for graph analytics, making it suitable for a wide range of use cases.

Recommended for

  • Developers and organizations needing a multi-model database solution
  • Projects requiring complex data analysis, including graph algorithms
  • Applications that can benefit from a flexible, schema-free data structure
  • Teams looking for scalability and horizontal expansion capabilities
  • Environments with diverse data representation needs where maintaining multiple databases is inefficient

ArangoDB videos

ArangoDB and Foxx Framework, deeper dive. WHILT#17

Apache Arrow videos

Wes McKinney - Apache Arrow: Leveling Up the Data Science Stack

More videos:

  • Review - "Apache Arrow and the Future of Data Frames" with Wes McKinney
  • Review - Apache Arrow Flight: Accelerating Columnar Dataset Transport (Wes McKinney, Ursa Labs)

Category Popularity

0-100% (relative to ArangoDB and Apache Arrow)
Databases
81 81%
19% 19
NoSQL Databases
87 87%
13% 13
Graph Databases
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

Share your experience with using ArangoDB and Apache Arrow. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare ArangoDB and Apache Arrow

ArangoDB Reviews

9 Best MongoDB alternatives in 2019
ArangoDB is a native multi-model DBMS system. It supports three data models with one database core and a unified query language AQL. Its query language is declarative which helps you to compare different data access patterns by using a single query.
Source: www.guru99.com
Top 15 Free Graph Databases
ArangoDB is 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. ArangoDB
ArangoDB vs Neo4j - What you can't do with Neo4j
Scalability needs and ArangoDB ArangoDB is cluster ready for graphs, documents and key/values. ArangoDB is suitable for e.g. recommendation engines, personalization, Knowledge Graphs or other graph-related use cases. ArangoDB provides special features for scale-up (Vertex-centric indices) and scale-out (SmartGraphs).

Apache Arrow Reviews

We have no reviews of Apache Arrow yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Arrow should be more popular than ArangoDB. It has been mentiond 38 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.

ArangoDB mentions (6)

View more

Apache Arrow mentions (38)

  • Unlocking DuckDB from Anywhere - A Guide to Remote Access with Apache Arrow and Flight RPC (gRPC)
    Apache Arrow : It contains a set of technologies that enable big data systems to process and move data fast. - Source: dev.to / 6 months ago
  • Using Polars in Rust for high-performance data analysis
    One of the main selling points of Polars over similar solutions such as Pandas is performance. Polars is written in highly optimized Rust and uses the Apache Arrow container format. - Source: dev.to / 8 months ago
  • Kotlin DataFrame ❤️ Arrow
    Kotlin DataFrame v0.14 comes with improvements for reading Apache Arrow format, especially loading a DataFrame from any ArrowReader. This improvement can be used to easily load results from analytical databases (such as DuckDB, ClickHouse) directly into Kotlin DataFrame. - Source: dev.to / about 1 year ago
  • Shades of Open Source - Understanding The Many Meanings of "Open"
    It's this kind of certainty that underscores the vital role of the Apache Software Foundation (ASF). Many first encounter Apache through its pioneering project, the open-source web server framework that remains ubiquitous in web operations today. The ASF was initially created to hold the intellectual property and assets of the Apache project, and it has since evolved into a cornerstone for open-source projects... - Source: dev.to / about 1 year ago
  • Arrow Flight SQL in Apache Doris for 10X faster data transfer
    Apache Doris 2.1 has a data transmission channel built on Arrow Flight SQL. (Apache Arrow is a software development platform designed for high data movement efficiency across systems and languages, and the Arrow format aims for high-performance, lossless data exchange.) It allows high-speed, large-scale data reading from Doris via SQL in various mainstream programming languages. For target clients that also... - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing ArangoDB and Apache Arrow, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Apache Ignite - high-performance, integrated and distributed in-memory platform for computing and transacting on...

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

Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.

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