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OrientDB VS Apache Arrow

Compare OrientDB VS Apache Arrow and see what are their differences

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OrientDB logo OrientDB

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

Apache Arrow logo Apache Arrow

Apache Arrow is a cross-language development platform for in-memory data.
  • OrientDB Landing page
    Landing page //
    2022-02-03
  • Apache Arrow Landing page
    Landing page //
    2021-10-03

OrientDB 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 OrientDB

Overall verdict

  • OrientDB is generally considered a strong choice for certain use cases.

Why this product is good

  • OrientDB is a multi-model database which supports graph, document, object, and key/value models. Its flexibility allows for more complex relationships between data entities and makes it suitable for applications requiring dynamic schema. It also boasts features like ACID transactions, horizontal scalability, and high performance querying.

Recommended for

  • Applications requiring complex relationships between data points
  • Organizations benefiting from a multi-model database
  • Projects that require scalability and high-performance query execution
  • Developers looking for a flexible schema architecture

OrientDB videos

+ Add

OrientDB - the 2nd generation of (MultiModel) NoSQL by Luigi Dell'Aquila

More videos:

  • Review - OrientDB Studio Overview
  • Review - OrientDB & Hazelcast: In-Memory Distributed Graph Database

Apache Arrow videos

+ Add

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 OrientDB and Apache Arrow)

OrientDB

Apache Arrow

Databases
73 73%
Databases
27% 27
NoSQL Databases
83 83%
NoSQL Databases
17% 17
Big Data
0 0%
Big Data
100% 100
Graph Databases
100 100%
Graph Databases
0% 0

User comments

Share your experience with using OrientDB and Apache Arrow. For example, how are they different and which one is better?
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Reviews

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

OrientDB Reviews

9 Best MongoDB alternatives in 2019
OrientDB is an open source NoSQL multi-model database. It allows organizations to unlock the true power of graph databases without the need to deploy multiple systems to handle other data types. This helps you to increase performance and security while supporting scalability.
Source: www.guru99.com
Top 15 Free Graph Databases
OrientDB is a 2nd Generation Distributed Graph Database with the flexibility of Documents in one product. It can store 220,000 records per second on common hardware. Even for a Document based database, the relationships are managed as in Graph Databases with direct connections among records. OrientDB Community Edition
Source: www.predictiveanalyticstoday.com

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 seems to be a lot more popular than OrientDB. While we know about 40 links to Apache Arrow, we've tracked only 1 mention of OrientDB. 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.

OrientDB mentions (1)

Apache Arrow mentions (40)

  • Show HN: Typed-arrow – compile‑time Arrow schemas for Rust
    I had no idea what Arrow is: https://arrow.apache.org or arrow-rs: https://github.com/apache/arrow-rs. - Source: Hacker News / about 2 months ago
  • Show HN: Pontoon, an open-source data export platform
    - Open source: Pontoon is free to use by anyone Under the hood, we use Apache Arrow (https://arrow.apache.org/) to move data between sources and destinations. Arrow is very performant - we wanted to use a library that could handle the scale of moving millions of records per minute. In the shorter-term, there are several improvements we want to make, like:. - Source: Hacker News / 2 months ago
  • 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 / 10 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 / 11 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 / over 1 year ago
View more

What are some alternatives?

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

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

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

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.

DuckDB - DuckDB is an in-process SQL OLAP database management system

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.

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