Software Alternatives & Reviews

Apache Ambari VS Google BigQuery

Compare Apache Ambari VS Google BigQuery and see what are their differences

Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.

A fully managed data warehouse for large-scale data analytics.
Apache Ambari Landing Page
Apache Ambari Landing Page
Google BigQuery Landing Page
Google BigQuery Landing Page

Apache Ambari details

Big Data Data Dashboard Data Science

Google BigQuery details

Data Dashboard Database Tools Big Data

Category Popularity

0-100% (relative to Apache Ambari and Google BigQuery)


These are some of the external sources and on-site user reviews we've used to compare Apache Ambari and Google BigQuery

Apache Ambari Reviews

We have no reviews of Apache Ambari yet.
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Google BigQuery Reviews

16 Top Big Data Analytics Tools You Should Know About
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.

Social recommendations and mentions

Based on our record, Google BigQuery seems to be more popular. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on Reddit, HackerNews and some other platforms. They can help you identify which product is more popular and what people think of it.

Apache Ambari mentions (0)

We have not tracked any mentions of Apache Ambari yet. Tracking of Apache Ambari recommendations started around Mar 2021.

Google BigQuery mentions (7)

  • Google Associate Cloud Engineer Exam Questions Part 1
    Answer: B Https:// - Source: / 29 days ago
  • The Data Trinity
    The storage component is simply where the data lives after extraction and loading. The most common artifact is a data warehouse or data lake depending on conceptual design. The most common services in this category are AWS Redshift, Google cloud Big query and Snowflake. - Source: / about 2 months ago
  • Utilizing BigQuery as a Data Warehouse in a distributed application
    To interact with BigQuery, first, we need to create a BigQuery account. For that, simply navigate to BigQuery in Google Cloud Platform, sign up for a GCP account, and create a new project there. We will be utilizing BigQuery within this project. - Source: / 3 months ago
  • Analytics Projects in Programmatic Space
    Https:// - Store all programmatic log levels on Google Bigquery, Build and deploy a propensity to purchase a model for predicting customer purchasing behavior using BigQuery ML and AI Platform. - Source: Reddit / 5 months ago
  • Google Cloud just posted this on their Twitter
    "Google Cloud’s databases and analytics products such as BigQuery, Dataflow, Pub/Sub and Firestore brought Theta Labs unlimited scale and performance, allowing them to: ...". - Source: Reddit / 6 months ago
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What are some alternatives?

When comparing Apache Ambari and Google BigQuery, you can also consider the following products

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Kubernetes - Kubernetes is an open source orchestration system for Docker containers

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.

Hadoop HDFS - The Apache HDFS is a distributed file system that makes it possible to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes.

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.

User reviews

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