Redis
MongoDB
ArangoDB
Apache Cassandra
PostgreSQL
neo4j
memcached
CouchBase
Pandas
NumPy
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.
PandasPandas might be a bit more popular than Redis. We know about 199 links to it since March 2021 and only 185 links to Redis. 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.
Hi there! I want to show off a little feature I made using hanami, htmx and a little bit of redis + sidekiq. - Source: dev.to / 20 days ago
Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance. - Source: dev.to / 22 days ago
The page 404s for me currently and it does not seem to be archived by the wayback machine either: https://web.archive.org/web/20240000000000*/https://redis.io/news/121. - Source: Hacker News / about 2 months ago
Redis - real time data storage with different data structures in a cache. - Source: dev.to / about 2 months ago
Redis.io no longer mentions open source. They have still not changed meta description on their page. It still says it is open source ^^ view-source:https://redis.io/. - Source: Hacker News / 2 months ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / 18 days ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / about 1 month ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 30 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 3 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
NumPy - NumPy is the fundamental package for scientific computing with Python
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
OpenCV - OpenCV is the world's biggest computer vision library
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
