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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Fivetran vs Google BigQuery

Fivetran vs Google BigQuery

OverviewComparisonAlternatives

Overview

Google BigQuery
Google BigQuery
Stacks1.8K
Followers1.5K
Votes152
Fivetran
Fivetran
Stacks116
Followers119
Votes0

Fivetran vs Google BigQuery: What are the differences?

## Introduction

Key differences between Fivetran and Google BigQuery:

1. **Data Integration vs. Data Warehouse**: Fivetran is a data integration tool that helps in extracting data from different sources, transforming it, and loading it into a destination of choice, while Google BigQuery is a data warehouse solution that allows for querying and analyzing data stored in it.
2. **Automated Data Pipelines vs. Query Execution**: Fivetran focuses on automating data pipelines by handling data extraction, transformation, and loading processes, making it easier for users to manage their data integration tasks, whereas Google BigQuery specializes in executing SQL queries on large datasets for analytics and reporting purposes.
3. **Pricing Model**: Fivetran typically charges based on the number of data connectors being used and the volume of data being processed, offering a straightforward pricing structure, while Google BigQuery charges based on the amount of data processed during queries and storage usage, providing a pay-as-you-go model for flexibility.
4. **Ease of Use**: Fivetran is known for its user-friendly interface and simple setup process, enabling users to quickly start extracting and syncing data without much technical expertise required, whereas Google BigQuery requires a deeper knowledge of SQL and data modeling to effectively utilize its features.
5. **Managed vs. Self-Managed**: Fivetran provides a fully managed service, handling all aspects of data integration and maintenance, reducing the need for manual interventions, while Google BigQuery is a self-managed platform where users have more control over data storage, partitioning, and optimization.
6. **Scalability**: Google BigQuery is designed to scale horizontally to handle vast amounts of data storage and queries efficiently, making it suitable for large enterprises with big data needs, whereas Fivetran is more focused on simplifying data integration tasks for small to medium-sized businesses.

In Summary, Fivetran and Google BigQuery serve distinct purposes in the data management landscape, with Fivetran specializing in data integration and automation, while Google BigQuery excels in data warehousing and query execution.

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Detailed Comparison

Google BigQuery
Google BigQuery
Fivetran
Fivetran

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

It helps you centralize data from disparate sources which you can manage directly from your browser. We extract your data and load it into your data destination.

All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.;Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.;Affordable big data- The first Terabyte of data processed each month is free.;The right interface- Separate interfaces for administration and developers will make sure that you have access to the tools you need.
Prebuilt connectors; Ready-to-query schemas; Automated schema migrations; Fully managed data; SQL-based transformations
Statistics
Stacks
1.8K
Stacks
116
Followers
1.5K
Followers
119
Votes
152
Votes
0
Pros & Cons
Pros
  • 28
    High Performance
  • 25
    Easy to use
  • 22
    Fully managed service
  • 19
    Cheap Pricing
  • 16
    Process hundreds of GB in seconds
Cons
  • 1
    You can't unit test changes in BQ data
  • 0
    Sdas
No community feedback yet
Integrations
Xplenty
Xplenty
Fluentd
Fluentd
Looker
Looker
Chartio
Chartio
Treasure Data
Treasure Data
Amazon DynamoDB
Amazon DynamoDB
AWS Lambda
AWS Lambda
Mailchimp
Mailchimp
Amazon S3
Amazon S3

What are some alternatives to Google BigQuery, Fivetran?

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Stitch

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Cloudera Enterprise

Cloudera Enterprise

Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

Airbyte

Airbyte

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

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