Software Alternatives & Startups

Fivetran VS Qubole

Compare Fivetran VS Qubole and see what are their differences

Fivetran

Fivetran offers companies a data connector for extracting data from many different cloud and database sources.

Rating
0 reviews
Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Rating
0 reviews
Pricing
Open source
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, Fivetran seems to be more popular. It has been mentioned 12 times since March 2021.

social mentions
12 vs 0
Data Integration popularity
100% vs 0%
alternatives listed
240+ vs 163

Base details

Website, pricing, platforms and company facts side by side.

Fivetran
Qubole
Website fivetran.com qubole.com
Pricing
Open source Official pricing
Company Startup from the United States · 250 - 499 employees · 2012 —
Listed in

Features and specs

What each product offers, as listed by its team.

Fivetran 6 features
Qubole 6 features
  • Automation
    Fivetran automates data integration, eliminating the need for manual coding and reducing maintenance overhead.
  • Scalability
    Fivetran can easily scale its services to handle growing data loads, making it suitable for businesses of various sizes.
  • Wide Range of Connectors
    It supports a broad array of data sources and destinations, allowing for diverse data pipelines.
  • Data Transformation
    Fivetran provides built-in data transformation capabilities, ensuring that data is in the correct format when it reaches the destination.
  • Real-Time Data Syncing
    Fivetran allows for near real-time data syncing, which is crucial for businesses that rely on up-to-date data for decision-making.
  • Reliability
    The service ensures data integrity and reliability, minimizing data loss during transfers.

Possible disadvantages

  • Cost
    Fivetran can be expensive, especially for small businesses or startups with limited budgets.
  • Limited Customization
    The platform offers limited options for customization, which might be a drawback for businesses with unique data integration needs.
  • Complex Setup for Non-Technical Users
    Despite its automation features, the initial setup can be complex for users without technical expertise.
  • Dependency on Third-Party Services
    Reliance on Fivetran means depending on a third party for crucial data integration tasks, which could be risky if the service faces downtime.
  • Data Latency for Some Sources
    While Fivetran supports near real-time syncing for many sources, some data sources might experience latency, affecting the freshness of the data.
  • Scalability
    Qubole allows seamless scalability, adjusting resources automatically based on workload, which facilitates efficient handling of large data sets and peaks in demand.
  • Multi-cloud Support
    Qubole offers support for multiple cloud providers, including AWS, Azure, and Google Cloud, giving users flexibility and freedom to choose or shift between cloud services.
  • Unified Interface
    The platform provides a unified interface for diverse data processing engines such as Apache Spark, Hadoop, Presto, and Hive, simplifying the management of big data operations.
  • Cost Management
    Qubole includes features for cost management and optimization, such as intelligent spot instance usage, which can reduce operational costs significantly.
  • Data Security
    Qubole offers robust security features, including encryption, access controls, and compliance with various regulations, which assists in maintaining data privacy and protection.
  • Integration Capabilities
    The platform supports integration with many other tools and services, which enables a streamlined pipeline for data extraction, transformation, loading (ETL), and analysis.

Possible disadvantages

  • Complex Setup
    For users unfamiliar with big data infrastructure and cloud platforms, the initial setup and configuration of Qubole may present a steep learning curve.
  • Cost Overruns
    Without careful management and monitoring, the automatic scaling and utilization of cloud resources can lead to unexpected and potentially high costs.
  • Dependency on Cloud Availability
    As a cloud-based platform, Qubole's performance and availability are contingent on the underlying cloud provider, which means service disruptions or performance issues in the cloud can affect Qubole’s operations.
  • Vendor Lock-in
    While Qubole supports multiple clouds, migrating away from the platform to another big data solution can be complex due to dependency on Qubole-specific configurations and optimizations.
  • Support and Documentation
    Some users have reported that the quality and depth of support and documentation provided by Qubole can vary, which may affect troubleshooting and learning.
  • User Interface
    While the interface is comprehensive, some users may find it less intuitive compared to other platforms, which can hinder ease of use and efficiency.

Analysis

An editorial look at what each product does well and who it suits.

Fivetran
Qubole

Overall verdict

  • Fivetran is generally regarded as a good solution for businesses looking for an automated, reliable, and easy-to-use data integration tool. It is particularly beneficial for companies that wish to reduce time and effort spent on managing data pipelines and ensuring accurate data transfer.

Why this product is good

  • Fivetran is considered good due to its ability to automate data integration processes, providing a seamless and efficient way to connect various data sources to your data warehouse. It offers pre-built connectors, automated schema management, and reliable data syncing, which reduces the need for manual coding and maintenance. Its robust security measures and scalability also contribute to its positive reputation.

Recommended for

    Fivetran is recommended for small to large businesses that require efficient data integration from multiple sources into their data warehouse. It is ideal for organizations looking for a fully managed service to simplify their ETL/ELT processes, especially those using cloud-based data warehousing solutions such as Snowflake, BigQuery, or Redshift.

Overall verdict

  • Qubole is generally considered a good platform for managing big data workloads, especially for businesses that seek flexibility and efficiency in processing and analyzing large-scale datasets. Its ability to automate and optimize workflows can lead to significant productivity gains and cost savings.

Why this product is good

  • Qubole is a cloud-based data platform that is designed to simplify and optimize big data processing. It allows data teams to manage and analyze large datasets efficiently by providing a unified interface for various data processing engines, including Apache Spark, Hive, and Presto. Its scalability, ease of integration with multiple cloud providers, automated data workflows, and support for machine learning models make it a valuable tool for organizations handling extensive data operations.

Recommended for

  • Data engineers and data scientists who need a robust platform for processing large volumes of data.
  • Organizations looking to leverage cloud-based solutions for big data processing and analytics.
  • Companies that want to integrate multiple data processing engines under a single management platform.
  • Businesses that require flexibility in scaling their data infrastructure in response to changing workloads.

Videos

Walkthroughs and reviews on video.

Fivetran 3 videos + Add
Qubole 3 videos + Add

Cloud Data Warehouse Benchmark Redshift vs Snowflake vs BigQuery | Fivetran

More videos

  • - Looker + Fivetran: Data Source to Dashboard in an Afternoon
  • - The Modern Data Stack: Fivetran + Looker + Snowflake

Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos

  • - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • - Democratizing Data with Qubole

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Fivetran
Qubole
100% 100%
0% 0%
0% 0%
100% 100%
100% 100%
ETL
0% 0%
0% 0%
100% 100%

User comments

Share your experience with using Fivetran and Qubole. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Fivetran no reviews yet
Qubole no reviews yet
  • Best ETL Tools: A Curated List
    estuary.dev · Apr 2025

    High costs: Fivetran’s pricing model, based on Monthly Active Rows (MAR), is one of the most expensive modern ELT vendors, often 5-10x the alternatives. Fivetran measures MARs based on its internal representation of...

  • Top 11 Fivetran Alternatives for 2024
    estuary.dev · Aug 2024

    Fivetran's pricing is determined by monthly active rows (MAR), which can be unpredictable because of the way Fivetran internally represents data and manages non-relational sources. Additionally, reducing latency...

  • 10 Best ETL Tools (October 2023)
    www.unite.ai · Oct 2023

    It is a cloud-based ETL solution that supports data integration with data warehouses like Redshift, BigQuery, Azure, and Snowflake. One of the top selling points of Fivetran is its array of data sources, with nearly...

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We have no reviews of Qubole yet. Be the first one to post

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Fivetran 12 mentions
Qubole 0 mentions
  • Sync Snowflake and Google Sheets
    Even looking past these limitations, internal scripts invariably require development and maintenance time, and as any developer knows, can break at the worst of times :) Method #2: Use Zapier? (https://zapier.com) Want to use Zapier to... - Source: Hacker News / over 3 years ago
  • Big problem with companies now is they hire data scientist for task that don't require data science practices.
    Disclaimer: I work for Fivetran, a data integration company. Source: about 4 years ago
  • I love data science but hate data engineering
    Disclaimer: I'm a product evangelist for a data integration company called Fivetran, so I'm shamelessly shilling here. Source: over 4 years ago

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Tracking Qubole since Mar 2021.

Alternatives to Fivetran and Qubole

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