Software Alternatives, Accelerators & Startups

Aerospike VS PyTorch

Compare Aerospike VS PyTorch and see what are their differences

Aerospike logo Aerospike

Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Aerospike Landing page
    Landing page //
    2023-09-16
  • PyTorch Landing page
    Landing page //
    2023-07-15

Aerospike videos

Aerospike Demo of Aggregation Querying

PyTorch videos

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Aerospike and PyTorch)
Databases
100 100%
0% 0
Data Science And Machine Learning
NoSQL Databases
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Aerospike and PyTorch

Aerospike Reviews

7 Best NoSQL APIs
The last piece of the puzzle when it comes to the attraction of Aerospike is its hybrid memory architecture. Aerospike takes an approach to storing data uniquely. It stores the index only in memory while the data persists in a solid state drive (SSD). While the magic in output lies deeper in the architecture, clients receive sub-millisecond latency read times at a throughput...
When to use Aerospike vs Redis | Aerospike
Need for strong data consistency If companies are building mission-critical applications where data consistency is a must, then Redis is not likely the right choice. Redis has not passed the Jepsen test for strong consistency (whereas Aerospike has). Redis supports eventual consistency, which can result in stale reads and even data loss under certain circumstances. Redis has...

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...

Social recommendations and mentions

Based on our record, PyTorch seems to be a lot more popular than Aerospike. While we know about 112 links to PyTorch, we've tracked only 8 mentions of Aerospike. 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.

Aerospike mentions (8)

  • Aerospike Driver for LINQPad
    Aerospike for LINQPad 7 is a data context dynamic driver for interactively querying and updating an Aerospike database using “LINQPad”. The driver is free. For more information go to this blog post. You can directly download the driver from the LINQPad NuGet manager. Source: about 1 year ago
  • Using In-Memory Databases in Data Science
    Aerospike is a real-time cloud structured platform with good performance capabilities. This IMDB platform allows enterprises to perform their operations in real time through the hybrid memory and parallelism model. - Source: dev.to / over 1 year ago
  • Block and Filesystem side-by-side with K8s and Aerospike
    Block storage stores a sequence of bytes in a fixed size block (page) on a storage device. Each block has a unique hash that references the address location of the specified block. Unlike a filesystem, block storage doesn't have the associated metadata such as format-type, owner, date, etc. Also, block storage doesn’t use the conventional storage paths to access data like a filesystem file. This reduction in... - Source: dev.to / over 1 year ago
  • Aerospike & IoT using MQTT
    This example shows how the Aerospike database can be easily and scalably used to store industrial time series data made available by the MQTT ecosystem. Aerospike plus its Community Time Series Client streamlines the storage and retrieval of the data, supporting the ability to both write and read millions of data points per second if required. - Source: dev.to / over 1 year ago
  • Building Large-Scale Real-Time JSON Applications
    Real-time large-scale JSON applications need reliably fast access to data, high ingest rates, powerful queries, rich document functionality, scalability with no practical limit, always-on operation, and integration with streaming and analytical platforms. They need all this at low cost. The Aerospike Real-time Data Platform provides all this functionality, making it a good choice for building such applications.... - Source: dev.to / almost 2 years ago
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PyTorch mentions (112)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 12 days ago
  • Mathematics secret behind AI on Digit Recognition
    Hi everyone! I’m devloker, and today I’m excited to share a project I’ve been working on: a digit recognition system implemented using pure math functions in Python. This project aims to help beginners grasp the mathematics behind AI and digit recognition without relying on high-level libraries like TensorFlow or PyTorch. You can find the complete code on my GitHub repository. - Source: dev.to / 11 days ago
  • Awesome List
    PyTorch - An open source machine learning framework. PyTorch Tutorials - Tutorials and documentation. - Source: dev.to / 18 days ago
  • Understanding GPT: How To Implement a Simple GPT Model with PyTorch
    In this guide, we provided a comprehensive, step-by-step explanation of how to implement a simple GPT (Generative Pre-trained Transformer) model using PyTorch. We walked through the process of creating a custom dataset, building the GPT model, training it, and generating text. This hands-on implementation demonstrates the fundamental concepts behind the GPT architecture and serves as a foundation for more complex... - Source: dev.to / 26 days ago
  • Building a Simple Chatbot using GPT model - part 2
    PyTorch is a powerful and flexible deep learning framework that offers a rich set of features for building and training neural networks. - Source: dev.to / about 1 month ago
View more

What are some alternatives?

When comparing Aerospike and PyTorch, 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.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

memcached - High-performance, distributed memory object caching system

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

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

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.