Kazuhm VS Databricks
Compare Kazuhm VS Databricks and see what are their differences
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Kazuhm
Activeeon
Mesosphere DCOS
Luigi
DepHell
Metaflow
Rancher
Shipper.software
Databricks
Google BigQuery
Looker
Jupyter
Presto DB
Informatica
Rakam
Concurrent
Kazuhm SaaS platform unifies the compute resources of an organization from desktops, to servers, to cloud, to edge, creating a private grid to place and process containerized workloads, optimize IT costs, security, and performance.
Through an easy user interface, customers leverage Kazuhm today to simplify Kubernetes and the deployment of popular data science applications, build their own private distributed compute networks, run workloads on-premises enabling the lowest possible latency, and easily manage multi-cloud and hybrid cloud environments.
Kubernetes-Made-Easy -- Set up and cluster deployment is super quick with container placement and host monitoring intuitively simple.
Multi-Cloud, Hybrid-Cloud Management -- Escape from vendor lock-in and centrally manage all your Public Cloud Hosts for FREE.
Data Science On Demand -- Simplify deployment of Spark and Jupyter and process workloads both on-premise and in the cloud.
Offset Cloud Costs -- Get “Cloud Smart”. Process containerized workloads on your Linux and Windows desktops and servers to offset cloud costs.
Low-Latency Workload Processing -- Reduce latency and improve performance by processing your data on-premise or at the edge – when milliseconds count.
Distributed Computing Anywhere -- Connect your desktops, both Windows and Linux, and servers or even your edge devices to create a powerful compute fabric.
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Based on our record, Databricks seems to be more popular. It has been mentiond 17 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.
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 / almost 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
Activeeon - ProActive Workflows & Scheduling is a java-based cross-platform workflow scheduler and resource manager that is able to run workflow tasks in multiple languages and multiple environments: Windows, Linux, Mac, Unix, etc.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Mesosphere DCOS - Mesosphere DCOS organizes your entire infrastructure as if it was a single computer.
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.
Luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs.
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.