Apache Arrow Reviews & Product Details

Apache Arrow is a cross-language development platform designed for in-memory data processing and efficient data interchange. It provides a standardized, language-independent columnar memory format that supports both flat and hierarchical data structures. This format is optimized for analytical operations on modern hardware, including CPUs and GPUs, facilitating high-performance data analytics and seamless integration across various data processing systems. Key Features and Functionality: - Columnar Memory Format: Arrow's in-memory columnar format is tailored for efficient analytic operations, enabling vectorized computations that leverage modern processor capabilities. - Zero-Copy Data Sharing: The platform allows for zero-copy reads, enabling rapid data access without the overhead of serialization and deserialization, thus enhancing performance in data-intensive applications. - Multi-Language Support: Arrow offers libraries in multiple programming languages, including C++, Java, Python, R, and more, ensuring broad compatibility and ease of integration into diverse development environments. - Interoperability with Data Formats: It provides tools for reading and writing various file formats such as CSV, Apache Parquet, and Apache ORC, facilitating smooth data interchange between different systems. - In-Memory Analytics and Query Processing: Arrow includes components for in-memory analytics and query processing, supporting efficient data manipulation and analysis directly in memory. Primary Value and Problem Solved: Apache Arrow addresses the challenges associated with processing large datasets by offering a unified, efficient in-memory data representation. By standardizing the columnar memory format and providing zero-copy data sharing, it significantly reduces the computational overhead typically involved in data serialization and deserialization. This leads to faster data processing and analytics, enabling developers to build high-performance applications that can handle complex data structures across various programming languages and platforms. Arrow's interoperability with existing data formats and its support for multiple languages make it a versatile tool for developers aiming to optimize data workflows and enhance the performance of data-driven applications.

Seller

The Apache Software Foundation

Discussions

Apache Arrow Community

Solution Type

Best-of-Breed

Value at a Glance

Averages based on real user reviews.

Perceived Cost

$$$$$

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User Insights

Average based on 31 real user reviews.

Perceived Cost

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Arati P.

Automation Developer

Enterprise (> 1000 emp.)

4/8/2021

"Portable computational libraries for DataScience and algorithm"

5/5

What do you like best about Apache Arrow?

Bring together database and data science communities to collaborate in the technology era. Open standard in-memory format. Helps in creating structured data processing applications. It supports languages like C, C++, Java, Perl, Python, and R Studio. Creates very fast algorithms. It's the main functional part of big data Hadoop, which is completely based on complex algorithms and huge data structures. It helps in big data transfer. Apache Hadoop community establishes with the arrow to down the arrow to columnar structure for memory processing and interchange. Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

Most have the database language and different types of programming languages. Complexity, need more support on technical language. And it weakly supports categorical data and has no query planning and eager evaluation model. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Arrow:

It is great for use when you have the Java, Python, and C++ integrated environment with complex algorithms to use. Review collected by and hosted on G2.com.

What problems is Apache Arrow solving and how is that benefiting you?

Mainly we solved algorithm problems and it is very helpful for complex data structures in databases. Review collected by and hosted on G2.com.

Kavin K.

Machine Learning Engineer

Enterprise (> 1000 emp.)

6/16/2021

"Apache Arrow is best for handling huge datasets"

5/5

What do you like best about Apache Arrow?

As I compared the results of Apache Arrow to HDF5, Arrow works the best for handling huge datasets, particularly in AWS EC2 instances. To work with Columnar based data storage, Arrow gives the best efficiency to do computations. Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

Though it does have the best efficiency in out-of-core computations like describe and count, it wouldn't work best for groupby computation which involves in-memory computations. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Arrow:

To work on huge datasets to solve business problems and to avoid in-memory computations, apache arrow works the best Review collected by and hosted on G2.com.

What problems is Apache Arrow solving and how is that benefiting you?

To handle business problems by computing huge datasets on-demand. I use apache arrow to store data in columnar level storage. Review collected by and hosted on G2.com.

Puja S.

Mid-Market (51-1000 emp.)

3/26/2021

"Accelerator and interface between language and system"

5/5

What do you like best about Apache Arrow?

The layout permits single instruction multiple data optimization.

We can create very fast algorithms by performing the same analytics workloads on multiple data points simultaneously. Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

High learning curve.

complexity

more documentation.

more developer support Review collected by and hosted on G2.com.

Nirmal R.

Android Engineer

Enterprise (> 1000 emp.)

8/2/2021

"Best tool for multilevel support."

3.5/5

What do you like best about Apache Arrow?

It supports multiple language support. Setup became straightforward. Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

Document guidance provides is not much informative. They should give some examples. Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Small-Business (50 or fewer emp.)

6/25/2021

"Apache Arrow: Little Data Accelator"

4/5

What do you like best about Apache Arrow?

A data model supporting complex types that handle both flat datatypes and JSON models. It handles large data sets very efficiently. Create an algorithm on multiple data sets simultaneously to do the analytics work. Its the language-independent and work completely on data. Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

It requires a high learning curve to work on the Apache Arrow. Documentation can be much clearer. Review collected by and hosted on G2.com.

Hemal J.

Software Engineer

Mid-Market (51-1000 emp.)

Originally submitted 7/13/2021

"good product but hangs little bit"

3.5/5

What do you like best about Apache Arrow?

UI is very good as compared to other performance is good if good hardware is provided Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

hangs so much some features are very complex to understand Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Mid-Market (51-1000 emp.)

7/13/2021

"Apache arrow review"

5/5

What do you like best about Apache Arrow?

open source and in-memory data representation that enables analytical systems and data sources to exchange and process data in real-time, simplifying and accelerating data access, without having to copy all data Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

THE RESULT SET IN APACHE ARROW FORMAT IS NOT SUPPORTED FOR THE PLATFORM." ERROR OCCURS WHEN USING PYTHON CONNECTOR WITH SNOWFLAKE Review collected by and hosted on G2.com.

Wadood S.

Student

Mid-Market (51-1000 emp.)

4/13/2021

Business partner of the seller or seller's competitor, not included in G2 scores.

"Brief review of Apache Arrow"

4.5/5

What do you like best about Apache Arrow?

It is easy to install and there are lot of FAQs online with the resources available to study and understand the tech stack Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

It does not have industry standardization which means, most companies use their own data analytic tools or tools from a Cloud Provider. Review collected by and hosted on G2.com.

Tigran M.

Java Software Engineer

Small-Business (50 or fewer emp.)

6/11/2021

"I had a little experience"

5/5

What do you like best about Apache Arrow?

I liked the variety of libraries for different languages Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

I didn't have any dislikes, I haven't explored a lot Review collected by and hosted on G2.com.

Karan P.

Technical Lead

Mid-Market (51-1000 emp.)

4/13/2020

"Great in memory data structure system for engineers. Great benefits."

4/5

What do you like best about Apache Arrow?

Many good things like its memory layout for random access, its efficient and fast interchange between systems. Overall a great experience using it. Review collected by and hosted on G2.com.

What do you dislike about Apache Arrow?

Nothing as such, it's a helping tool to be used. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Arrow:

If you use complex data structures this is the tool for you. Great experience so far. Review collected by and hosted on G2.com.

What problems is Apache Arrow solving and how is that benefiting you?

It has a flexible structured data model which supports complex types as well as real world JSON data as well. This was not so easy before using it. Review collected by and hosted on G2.com.