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.
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Based on our record, Redis seems to be a lot more popular than graph-tool. While we know about 216 links to Redis, we've tracked only 4 mentions of graph-tool. 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.
Of course, these examples are just toys. A more proper use for asynchronous generators is handling things like reading files, accessing network services, and calling slow running things like AI models. So, I'm going to use an asynchronous generator to access a networked service. That service is Redis and we'll be using Node Redis and Redis Query Engine to find Bigfoot. - Source: dev.to / about 11 hours ago
Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / about 12 hours ago
Real-time serving: Many push processed data into low-latency serving layers like Redis to power applications needing instant responses (think fraud detection, live recommendations, financial dashboards). - Source: dev.to / 14 days ago
Redis® Cluster is a fully distributed implementation with automated sharding capabilities (horizontal scaling capabilities), designed for high performance and linear scaling up to 1000 nodes. . - Source: dev.to / about 1 month ago
Instead of spinning up Redis, use an unlogged table in PostgreSQL for fast, ephemeral storage. - Source: dev.to / about 2 months ago
Some Python libraries have a C/C++ core that relies on libraries such as Cairo and Boost and many others. Such dependencies are not installable with pip/venv simply because they are not Python packages. If you want to try one example, have a go on installing Graph-Tool using pip. Source: over 2 years ago
Do they offer the full feature set of graph-tools? https://graph-tool.skewed.de/. Source: over 2 years ago
Graph-tool - it does only 2D plots and has very slow interactive graphs. Source: about 3 years ago
Graph-tool: This is the one I use the least, although it is probably one of the most powerful. It lets you quickly run advanced community detection analyses like stochastic block models, hierarchical partitions, etc. It also has a fantastic visualization suite for making gorgeous figures. It used to be a pain in the ass to compile, which is why I ended up sinking the time into igraph, although I understand that... Source: about 4 years ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
NetworkX - NetworkX is a Python language software package for the creation, manipulation, and study of the...
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
LemonGraph - An embedded transactional graph engine for Python.