Software Alternatives, Accelerators & Startups

DynamoDB VS Google BigQuery

Compare DynamoDB VS Google BigQuery and see what are their differences

DynamoDB logo DynamoDB

Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • DynamoDB Landing page
    Landing page //
    2023-03-18
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

DynamoDB videos

#13 - Amazon DynamoDB Basics In Under 5 Minutes [Tutorial For Beginners]

More videos:

  • Review - AWS re:Invent 2018: Amazon DynamoDB Deep Dive: Advanced Design Patterns for DynamoDB (DAT401)
  • Review - What is Amazon DynamoDB?

Google BigQuery videos

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Category Popularity

0-100% (relative to DynamoDB and Google BigQuery)
Databases
100 100%
0% 0
Data Dashboard
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

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Reviews

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

DynamoDB Reviews

9 Best MongoDB alternatives in 2019
Amazon DynamoDB is a nonrelational database. This database system provides consistent latency and offers built-in security, and in-memory caching. DynamoDB is a serverless database which scales automatically and backs up your data for protection
Source: www.guru99.com

Google BigQuery Reviews

Top 6 Cloud Data Warehouses in 2023
You can also use BigQuery’s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or “heavy” queries that operate using a large set of data. This means it’s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io
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, DynamoDB should be more popular than Google BigQuery. It has been mentiond 104 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.

DynamoDB mentions (104)

  • Understanding KeyConditionExpression and FilterExpression in DynamoDB
    DynamoDB is a powerful NoSQL database provided by AWS, designed to handle large amounts of data efficiently. However, for newcomers, understanding the nuances of querying DynamoDB tables can be challenging, particularly when it comes to the differences between KeyConditionExpression and FilterExpression. This blog post aims to clarify these concepts and provide practical examples of their usage. - Source: dev.to / 19 days ago
  • Event-Driven Architecture on AWS
    Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / about 1 month ago
  • How to Build Your Own ChatGPT Clone Using React & AWS Bedrock
    The first is AWS DynamoDB which is going to act as our NoSQL database for our project which we’re also going to pair with a Single-Table design architecture. - Source: dev.to / about 1 month ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    DynamoDB - 25GB NoSQL DB EC2 - 750 hours per month of t2.micro or t3.micro(12mo). 100GB egress per month. - Source: dev.to / 4 months ago
  • Starting My AWS Certification Journey as a Certified Cloud Practitioner
    After two years, I moved to a Web3 startup where I was given a lead software engineer role. This new role gave me more hands-on experience with AWS, where I've learned to implement serverless technologies like Lambda and DynamoDB. - Source: dev.to / 6 months ago
View more

Google BigQuery mentions (35)

  • Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
    Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 9 months ago
  • Modern data stack: scaling people and technology at FINN
    Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 9 months ago
  • Running Transformations on BigQuery using dbt Cloud: step by step
    Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 10 months ago
  • Do I need a cloud computing–based data cloud company
    You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 11 months ago
  • I used ChatGPT to get an Internship
    Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 11 months ago
View more

What are some alternatives?

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

AWS Lambda - Automatic, event-driven compute service

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

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.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

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.