I like best about Apache SystemML is its seamless scalability from single machines to large clusters and its integration with Apache Spark for efficient big data processing. Review collected by and hosted on G2.com.

What do you dislike about Apache SystemML?

I dislike about Apache SystemML is its steep learning curve for beginners. It requires users to be comfortable with coding and big data frameworks, which can be challenging for those new to machine learning or big data tools. Review collected by and hosted on G2.com.

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

Apache SystemML solves the problem of efficiently running machine learning algorithms on large databases. By seamlessly scaling from single machines to large clusters and optimizing resource use, it handles big data tasks effectively. This benefits users by enabling faster processing times and more accurate machine learning models, which is crucial for data-driven decision-making. Review collected by and hosted on G2.com.

RK

RAKESH K.

Assistant Professor and Junior Research Fellow

Education Management

Mid-Market (51-1000 emp.)

3/5/2024

"Apache SystemML is Good to work with Machine Learning along with Bigdata"

4/5

What do you like best about Apache SystemML?

Apache SystemML is from IBM which declared it as open source. Apache SystemML is good platform to solve Machine Learning problems. In Machine Learning we need of a lot of data and handling those bigdata is not an easy task which can be done seamlessly with Apache SystemML. It is also helpful for data scientist or engineers. It customizes and optimizes algorithms based on there characteristics. It supports popular R, Python language which is helpful also. With the add on help of apache spark it flourish it's accuracy well. Apache SystemML automatically generate hybrid runtime plans ranging from single node, in memory computation, distributed computation on Apache Hadoop and Spark. Review collected by and hosted on G2.com.

What do you dislike about Apache SystemML?

Apache SystemML is still struggling for customer acquisition. Also it lacks of project collaboration. Sometimes it seems slow while processing data. Though there is documentations but it needs an update periodically. Review collected by and hosted on G2.com.

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

We do work in the field of Machine Learning with this tool which helps us to optimize using optimizers functions. Using Apache SystemML we create and extend Machine Learning frameworks which are commercial friendly and scalable. We use DML, optimizer stack and LDescribe for efficiently use ML algorithms. Review collected by and hosted on G2.com.

ON

Onkar N.

Associate Software Engineer

Mid-Market (51-1000 emp.)

7/26/2024

"Scalable and Flexible ML for Big Data"

5/5

What do you like best about Apache SystemML?

I like that Apache SystemML lets you write ML models in a simple way and handles the complex details of execution and scaling for you. Review collected by and hosted on G2.com.

What do you dislike about Apache SystemML?

Another downside is that Apache SystemML can be less flexible for custom ML algorithms compared to lower-level libraries, and its performance may vary based on how well the automatic optimization aligns with specific use cases. Review collected by and hosted on G2.com.

UC

Verified User in Computer & Network Security

Small-Business (50 or fewer emp.)

1/3/2024

"Very Good Platform"

4.5/5

What do you like best about Apache SystemML?

As we know, machine learning deals with Big Data, so Apache SystemML is a platform that mainly focuses on the big data required to create a machine learning module. This ensures greater accuracy. It can run over Apache Spark. Review collected by and hosted on G2.com.

What do you dislike about Apache SystemML?

Don't have the complete guide documentation and it's not highly available. Review collected by and hosted on G2.com.