memcached
Redis
MongoDB
Aerospike
PostgreSQL
Apache Cassandra
Apache Ignite
CouchBase
Databricks
Google BigQuery
Looker
Jupyter
Presto DB
Informatica
Rakam
Concurrent
memcached DatabricksBased on our record, memcached should be more popular than Databricks. It has been mentiond 29 times since March 2021. 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.
Distributed caching Consistent hashing is a popular technique for distributed caching systems like Memcached and Dynamo. In these systems, the caches are distributed across many servers. When a cache miss occurs, consistent hashing is used to determine which server contains the required data. This allows the overall cache to scale to handle more requests. - Source: dev.to / 6 days ago
Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs. - Source: dev.to / 3 months ago
Stores session state in a session store like Memcached or Redis. - Source: dev.to / 5 months ago
Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers. - Source: dev.to / 10 months ago
In server-side authentication, the session state is stored on the server-side, which can be scaled horizontally across multiple servers using tools like Redis or Memcached. - Source: dev.to / 10 months ago
Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: about 1 year ago
Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / over 1 year ago
Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / almost 2 years ago
Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / about 2 years ago
I am considering Hex, Deepnote, and possibly Databricks. Does anyone have any experience using the first 2 (i have worked with Databricks in the past) and have thoughts they can share? The company isn't doing any fancy data science so far so I mostly want it for deep product analytics which I can turn into reports that are easily shareable across the org. That being said, I do want to get into statistical... Source: about 2 years ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
