Fivetran

Fivetran

About TrustRadius Scoring
Score 8.4 out of 100
Fivetran

Overview

Recent Reviews

Highly recommend Fivetran

8 out of 10
December 02, 2021
We use Fivetran as our Extract Transform Load provider bringing data from all our various third-party services into our Data Warehouse in …
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Popular Features

View all 12 features

Connect to traditional data sources (7)

8.7
87%

Simple transformations (6)

8.0
80%

Data model creation (6)

7.6
76%

Connecto to Big Data and NoSQL (5)

7.4
74%

Reviewer Pros & Cons

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Video Reviews

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Pricing

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Starter

$1.00

Cloud
per credit

Standard

$1.50

Cloud
per credit

Enterprise

$2.00

Cloud
per credit

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

Features Scorecard

Data Source Connection

8.0
80%

Data Transformations

8.0
80%

Data Modeling

8.0
80%

Data Governance

7.5
75%

Product Details

What is Fivetran?

Fivetran replicates applications, databases, events and files into a high-performance data warehouse, after a five minute setup. The vendor says their standardized cloud pipelines are fully managed and zero-maintenance.

The vendor says Fivetran began with a realization: For modern companies using cloud-based software and storage, traditional ETL tools badly underperformed, and the complicated configurations they required often led to project failures. To streamline and accelerate analytics projects, Fivetran developed zero-configuration, zero-maintenance pipelines to deliver data into modern cloud warehouses.

Shaped by the real-world needs of data analysts and business intelligence users, Fivetran technology promises to enable organizations to control their data without complex engineering and ultimately supports data-backed decisions and company culture.

Fivetran Features

  • Supported: Five-minute setup
  • Supported: Complete replication from any source
  • Supported: Fully managed 24x7
  • Supported: Normalized schemas from denormalized APIs
  • Supported: Automatic schema migrations

Fivetran Competitors

Fivetran Technical Details

Deployment TypesSaaS
Operating SystemsUnspecified
Mobile ApplicationNo
Supported CountriesWorldwide
Supported LanguagesEnglish

Comparisons

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Frequently Asked Questions

What is Fivetran's best feature?

Reviewers rate Metadata management highest, with a score of 9.

Who uses Fivetran?

The most common users of Fivetran are from Mid-sized Companies (51-1,000 employees) and the Computer Software industry.

Reviews and Ratings

 (25)

Ratings

Reviews

(1-8 of 8)
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Uddipan Mukherjee | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Fivetran is used as a near real-time data replication solution between several source systems and organization-wide databases. Sources include traditional RDBMS, APIs, SAP Hana, etc. Fivetran is a reliable, and available service that did not result in any performance or data issues during its tenure with the data platform. It also supports some data transformations which are helpful to some use cases.
  • Near real time Data replication
  • Basic standardization
  • Availability of a wide variety of ingestion plugins
  • View based ingestion from RDBMS
  • Detailed Logging
  • API support
Fivetran is very well suited for any near real-time ingestion requirements for available plugins. Do not use it for complex data standardization as it only supports some features with that respect. Fivetran provides the required information on data volume, cost applicable, which is helpful to plan future ingestions. Sometimes historical refresh cost goes very high, but users also can be trained to save cost with appropriate measures.
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use it for the majority of our ETL to our data warehouse
  • Simplified ETL from a wide range of data sources
  • Stable and painless data pipeline
  • Granular control over what parts of the data source are loaded
  • More detailed logging
  • More flexible choices for time range over which records are synced
  • More options for masking and excluding sensitive data
When you need a super quick and easy way to load data from a third-party source to a warehouse when a delay of up to an hour is an option, Fivetran is the way to go. It is shockingly easy and yet does support a fair amount of sophistication at a reasonable cost. It lacks automation and infrastructure as code abilities and internal transformations are limited, but it shines at batch extraction and handles schema changes for you very smoothly.
Score 8 out of 10
Vetted Review
Verified User
Review Source
We use Fivetran at my organization to securely replicate data from our production databases to our data warehouses in Snowflake, syncing production data at regular intervals on a daily schedule. This allows us to efficiently move data without impacting our production systems and allows us to keep more historically complete records of the life of data that exists in our production databases.
  • Allows triggering of transformations using basic SQL transformations performed when new data is loaded or synced over
  • Supporting data sync without affecting production databases availability or increasing load on production databases
  • Providing out-of-the-box connectors for quick and easy connection to a variety of commonly used databases
  • Supporting a variety of data sources (not only databases but also files like JSON or CSV files with exported data
  • Doesn't include support for a Kinesis stream as a data source so couldn't be used for some use cases under consideration
  • Doesn't support the use of "BEFORE DELETE" triggers
  • No support for serverless Aurora
Fivetran is a good choice if you want to get started quickly with replicating production transactional database tables to Snowflake with minimal impact on production. Setup is fast and Fivetran provides a user-friendly interface that can be used to resync individual tables if necessary. It's a good solution for a mature database schema where certain tables hold a very large amount of data, which when replicated into a system like Snowflake allows users to execute queries against the dataset that would otherwise be very slow and not perform well directly against the production database.
December 02, 2021

Highly recommend Fivetran

Score 8 out of 10
Vetted Review
Verified User
Review Source
We use Fivetran as our Extract Transform Load provider bringing data from all our various third-party services into our Data Warehouse in Microsoft Azure. Personally, I've used it extensively with Twilio's sendgrid connector in bringing and formatting all of our email and notification data into the warehouse for data analysts internally to run more extensive analysis on it.
  • UI is very clean.
  • Documentation is easy to use.
  • Plenty of connectors for different third party services.
  • Honestly, not much they're already crushing it!
  • If I had to say one thing, I guess I would say make it more accessible to non-data engineers.
I think it's suited best for what it was built for, ETL pipelines expedited. If you are a startup that has a software product with various different data sources that you need to quickly and reliably bring all together to some kind of centralized data store, Givetrain is well suited for this use case. If that isn't part of your business needs to do this data consolidation before any analysis it probably isn't well suited for your use case.
Murray Clear | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Fivetran is perhaps the best metadata service we have had the opportunity to work with. We liked this software for the ease it promotes when managing communication data from the panel, since we can freely export them to other services, to synchronize them with other devices that use similar software and to convert the data without losing them. Data replication has a very low impact, which is helpful in preventing accidents from occurring during such operations. There is complete accessibility to all SQL documents being managed within the platform, and by integrating it with services such as Microsoft Access or others it is easy to manage it without altering the information in those documents. The platform makes complete replication of all data loaded into it by default, so there is no need to worry about incomplete or damaged files.
  • Fivetran connects all data through an excellent mapping system, with which it is feasible to create maps in case we need to analyze them later, either in real time or waiting for the complete data update until a certain period of time.
  • The accessibility permissions to the information within Fivetran are generally intuitive, and help not only to keep the information entirely secure, but also to be easily identified as the allowed managers for its administration.
  • The high scalability of data replication operations is ideal for creating backups of information, whether or not you will be working in the cloud, so that each source system is kept sufficiently protected so that there is no major impact when an incident is encountered.
  • Overall we have been pleased with the ability demonstrated by the Fivetran user support representative, as he was able to provide us with quick solutions to fix our issues with the platform, and that they were not really a mistake about the software and its structure, but a mistake on our part during the configuration process.
  • Fivetran has helped us to mobilize much more optimally all the databases that we replicate from the different parts of our system, so that we cover a data flow not only better, but our own, where the ability to customize the databases is the predominant concept and the one that helps us to continue improving in our management.
  • Data is not automatically extracted, and this can make it quite difficult to collect metrics for analysis from one document to another. In any case, this can be a major problem if you are working with other developers, since they would not be able to see the entire management of others if you want to attach certain information in someone else's document.
  • It lacks many integrations that would make working with data more extensive and would expand the possibilities of migrating information, as shown by the need to work with data to CRM or online security tools.
  • In Fivetran there are no processes in place that allow the team leader to review databases for approval prior to their initiation into the company's traffic, and this is very problematic because of not being able to create a safe space for data reviews from others.
Mostly Fivetran can be useful for working with risk reduction operations during agile data analysis processes. I.e., in the short term the heaviest data movement operations would be safe. If you need to create an automated infrastructure for the data, the ability to create data list transformations in SQL is useful for keeping the work integrable or with schema changes. For situations that require a lot of speed: setting up the Fivetran platform is very easy, as you only need to authenticate the sources of the data to start working, and this is excellent for covering fast storage operations.
Sudarshan Kothari | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
Fivetran has lots of digital connectors available with them required in our organization to make business decisions. Our Data management is the main consumer of the product, which then widely gets consumed in the organization's analytical format to make strategies. We are data-driven digital marketers that rely on data to make decision. The sources are expanding and handling them individually makes them very challenging and that's where Fivetran helps us solve the problem.
  • Seamless connector for data requirements
  • Custom reports
  • Database Connection
  • Change Lod
  • User-based control
Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.
Score 9 out of 10
Vetted Review
Verified User
Review Source
Fivetran is used by our reporting and analytics team to ingest data from multiple SaaS, Ad platform, and internal data sources. Fivetran supports our ELT approach using delivered connectors for most of our data sources.
  • Easily connects to source data using delivered connectors
  • Transforms data into standard models and schemas
  • Has very good documentation to help quickly setup connectors
  • Alerting and notification could be enhanced and be more timely in some cases
  • The error messages when there are connector setup issues could be more clear
[Fivetran is] very well suited when you are using popular and common data sources, such as the major ad platforms, and SaaS platforms such as Salesforce.
If the majority of your data sources are custom internal applications or databases, may be less value as you aren't leveraging the delivered connectors.
Scott Laronge | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
We use it to sync a MySQL instance to a redshift cluster so we can run analytics against a non-prod environment.
  • Quick replication of data with minimal lag.
  • Automated reporting if data is out of date.
  • The customer support team is relatively good.
  • A full schema refresh takes us two-three days and knocks us offline from monitoring up-to-date business KPIs, running updated analyses, etc. This is likely due to us having massive amounts of data (from a count(1) perspective, not size of tables perspective).
  • There's little to no progress estimate on the front end UI to see how long this refresh might take and you need to enable back end logging in Amazon to see where it's at in the sync process and derive rough estimates of completion time.
Fivetran works well when you have a lot of data in different places and want to get it all in one spot. I don't think it's as necessary if you have one cluster that needs to be replicated against and the data could wait a day. In this instance, there are other tools.