Last updated on
Ratings
Google Cloud Datalab description
Google Cloud Datalab is a tool that helps you analyze and visualize large amounts of data. It runs on your own computers or Google Cloud Platform and easily connects with other Google services. You can explore data, build charts, and even create machine learning models using simple code and pre-built templates. This makes it easier for your teams to understand complex data and make better decisions.
Who is Google Cloud Datalab best for
Google Cloud Datalab is a valuable tool for data scientists and analysts working with large datasets within the Google Cloud Platform. Users appreciate the seamless integration with other GCP services and the user-friendly Jupyter notebook interface. However, some have noted difficulties integrating with non-Google services and a steep learning curve. The platform excels in interactive data exploration and visualization but may have limitations with very large datasets.
-
Best for small to mid-sized businesses needing basic data analysis within the Google Cloud ecosystem.
-
Limited industry-specific features; suitable for general data analysis across various sectors.
Google Cloud Datalab features
| Supported Cloud Datalab offers a cloud-based platform for data analysis and visualization, integrating with GCP services. |
| Supported Datalab supports interactive data discovery and visualization via Matplotlib and Google Charts. |
| Supported Datalab supports scalable visualizations via integrations with libraries like matplotlib. |
Google Cloud Datalab reviews
We've summarised 72 Google Cloud Datalab reviews (Google Cloud Datalab G2 reviews) and summarised the main points below.
- Seamless integration with other Google Cloud services (BigQuery, Cloud Storage, Dataflow).
- User-friendly Jupyter notebook interface for interactive data exploration.
- Rich set of pre-installed libraries for data analysis (TensorFlow, pandas, NumPy, matplotlib).
- Facilitates collaboration on data analysis and machine learning tasks.
- Difficult integration with non-Google services.
- Steep learning curve, especially for those unfamiliar with Jupyter or GCP.
- Limited scalability for large datasets or computationally intensive tasks.
- VPN connectivity issues can disrupt workflow.
Google Cloud Datalab alternatives
Databricks Data Intelligence PlatformBetter fit for enterprise companies and the software and IT industries. Boasts a higher average rating and has more momentum. Stronger data governance and AI features.Read more
Vertex AI NotebooksBetter for enterprise companies and machine learning model deployment. A strong Google Cloud Datalab competitor for collaborative model building.Read more
Salesforce PlatformBetter for enterprise companies and various industries. Focuses on CRM, application building, and automation. More established, faster growing Salesforce Platform alternative. Users appreciate automation and operating system unification. Negative pricing sentiment.Read more
TableauBetter for enterprise companies. A more user-friendly alternative to Google Cloud Datalab, with a drag-and-drop interface. Broader industry applicability. More established, with significantly more momentum.Read more
LookerBetter for business intelligence and reporting. More user-friendly, especially for non-technical users. A better fit for medium and large companies. Broader industry applicability. More positive pricing sentiment.Read more
SnowflakeBetter for enterprise companies. A Google Cloud Datalab alternative, Snowflake offers broader industry coverage and better scalability. It has more momentum and higher ratings. Stronger SQL support and data warehousing integration are key differentiators.Read more
Google Cloud Datalab FAQ
What is Google Cloud Datalab and what does Google Cloud Datalab do?
Google Cloud Datalab is a cloud-based interactive data analysis and visualization tool. It leverages Jupyter notebooks, integrates with Google Cloud services, and offers pre-built libraries for tasks like data exploration, chart creation, and machine learning model development. This enables teams to understand complex data and make data-driven decisions.
How does Google Cloud Datalab integrate with other tools?
Google Cloud Datalab seamlessly integrates with other Google Cloud services like BigQuery, Cloud Storage, and Dataflow, facilitating efficient data analysis workflows. It leverages a Jupyter notebook interface and offers pre-built libraries for tasks such as machine learning.
What the main competitors of Google Cloud Datalab?
Top alternatives to Google Cloud Datalab include Databricks, Vertex AI Notebooks, Tableau, Looker, and Snowflake. These competitors offer similar data analysis and visualization capabilities, often with varying strengths in scalability, integrations, and user-friendliness.
Is Google Cloud Datalab legit?
Yes, Google Cloud Datalab is a legitimate tool developed by Google. It's a safe and integrated platform within the Google Cloud ecosystem for data analysis and visualization, especially suited for users already working with Google Cloud services.
How much does Google Cloud Datalab cost?
Google Cloud Datalab's pricing is not publicly available. You may need to contact Google Cloud sales for datalab product pricing or further information regarding whether the product is worth the investment.
Is Google Cloud Datalab customer service good?
Customer reviews indicate that Google Cloud Datalab's customer service is generally positive, providing easy and informative support. However, the initial setup process may involve extensive questioning that some users find invasive or unnecessary.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.