What is Deepnote and what are its top alternatives?
Top Alternatives to Deepnote
JupyterThe Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media. ...
Apache ZeppelinA web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. ...
SageMathIt is a free open-source mathematics software system licensed under the GPL. It builds on top of many existing open-source packages: NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, R and many more. ...
FranchiseChart with a single click. Compare queries side by side. Download your work and share it with anyone. If your data is in a CSV, JSON, or XLSX file, loading it is as simple as dropping the file into Franchise. ...
PolynoteIt is a different kind of notebook. It supports mixing multiple languages in one notebook, and sharing data between them seamlessly. It encourages reproducible notebooks with its immutable data model. ...
VayuIt is an end-to-end tool for data science, without writing any code. Import, prepare, analyze, visualize and share in just a few clicks. Build interactive reports, automate workflows and share templates. ...
StarboardIt is fully in-browser literate notebooks like Jupyter Notebook. It's probably the quickest way to visualize some data with interactivity, do some prototyping, or build a rudimentary dashboard. ...
mljar MercuryIt is the easiest way to turn your Python Notebooks into interactive web applications and publish to the cloud. It is dual-licensed. The main features are available in the open-source version. It is perfect for quick demos, educational purposes, sharing notebooks with friends. ...
Deepnote alternatives & related posts
- In-line code execution using blocks18
- In-line graphing support10
- Can be themed7
- Multiple kernel support6
- Best web-browser IDE for Python3
- Export to python code3
- LaTex Support2
- HTML export capability1
- Multi-user with Kubernetes1
related Jupyter posts
From my point of view, both OpenRefine and Apache Hive serve completely different purposes. OpenRefine is intended for interactive cleaning of messy data locally. You could work with their libraries to use some of OpenRefine features as part of your data pipeline (there are pointers in FAQ), but OpenRefine in general is intended for a single-user local operation.
I can't recommend a particular alternative without better understanding of your use case. But if you are looking for an interactive tool to work with big data at scale, take a look at notebook environments like Jupyter, Databricks, or Deepnote. If you are building a data processing pipeline, consider also Apache Spark.
Edit: Fixed references from Hadoop to Hive, which is actually closer to Spark.
Jupyter Anaconda Pandas IPython
A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.
The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead
- In-line code execution using paragraphs7
- Cluster integration5
- Multi-User Capability4
- In-line graphing4
- Zeppelin context to exchange data between languages4
- Privacy configuration of the end users2
- Execution progress included2
- Multi-user with kerberos2
- Allows to close browser and reopen for result later2
related Apache Zeppelin posts
related SageMath posts
related Franchise posts
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