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Best in Class at Competitive Price
What do you like best about the product?
Fivetran is a best in class product, that offers services to our smaller use company at a reduced price rate.
What do you dislike about the product?
Like any other pay per usage software, lower usage levels result in longer support times.
What problems is the product solving and how is that benefiting you?
Fivetran takes care of the extracting and loading in the modern data stack. It allows us to get the data from disparate systems in one place for analysis.
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Quick to Set up - very well integrated
What do you like best about the product?
Speedy for the data team to set up and connects perfectly with snowflake. We have been able to move into BI tooling quickly as a result of building this layer.
What do you dislike about the product?
No complaints of the software at this time and the integrations and onboarding team have been excellent.
What problems is the product solving and how is that benefiting you?
Connecting and data with snowflake and handling ELT and DBT.
The leading low-code data ingestion solution
What do you like best about the product?
Fivetran offers a truly competitive solution for data integration, in particular when you're looking to connect to a source application and ingest that data into a Data Warehouse or Data Lake and to do that with minimal development/configuration/customization. The best features are:
- The number of application connectors. There are hundreds of connectors to both SaaS/Web based applications such as Salesforce, Coupa, JIRA, etc as well as database and on-premise, of particular interest to us was SAP
- The ease of configuration/setup to integrate to a source connection and the time taken to ingest and synch to a destination connection
- The Data Change Capture (CDC) feature for many of the connectors (not all connectors offer CDC) is very slick and will easily manage INSERTS, UPDATES, DELETES in your data and track the date/time of those changes
- The ability to connect to SAP and manage CDC through the database logs. This provides a minimal intrusion feature that is not reliant on many other SAP connectors/integrations which go through the API layer (RFC)
- The SAP integration can ingest many of the complicated SAP objects such as long-text data/tables involving structures like pool and cluster
- The easy UI that allows you to change basic configurations such as frequency of update, tables/fields required to ingest and usage/billing
- Technical Support is excellent and responsive, although you probably have to be on the Business Critical support to realize this
- Integration with dbt and an emerging "Marketplace" of pre-built models and transformations
- The number of application connectors. There are hundreds of connectors to both SaaS/Web based applications such as Salesforce, Coupa, JIRA, etc as well as database and on-premise, of particular interest to us was SAP
- The ease of configuration/setup to integrate to a source connection and the time taken to ingest and synch to a destination connection
- The Data Change Capture (CDC) feature for many of the connectors (not all connectors offer CDC) is very slick and will easily manage INSERTS, UPDATES, DELETES in your data and track the date/time of those changes
- The ability to connect to SAP and manage CDC through the database logs. This provides a minimal intrusion feature that is not reliant on many other SAP connectors/integrations which go through the API layer (RFC)
- The SAP integration can ingest many of the complicated SAP objects such as long-text data/tables involving structures like pool and cluster
- The easy UI that allows you to change basic configurations such as frequency of update, tables/fields required to ingest and usage/billing
- Technical Support is excellent and responsive, although you probably have to be on the Business Critical support to realize this
- Integration with dbt and an emerging "Marketplace" of pre-built models and transformations
What do you dislike about the product?
- The support for dbt does not currently include Azure Synapse, which is what we are using for our Data Platform
- The frequency of refresh configuration is good, but it would also be good if you could have a "Date/Time" of refresh rather than a synch period such as "Every 1 hour, every 24 hours, etc"
- Would be nice if Fivetran could support the ingestion of SAP structure fields/tables
- Would be great if Fivetran could ingest SAP BW data
- The frequency of refresh configuration is good, but it would also be good if you could have a "Date/Time" of refresh rather than a synch period such as "Every 1 hour, every 24 hours, etc"
- Would be nice if Fivetran could support the ingestion of SAP structure fields/tables
- Would be great if Fivetran could ingest SAP BW data
What problems is the product solving and how is that benefiting you?
- We can now ingest data from some of our enterprise applications where it has been extremely difficult or near impossible previously. Many of the previous "integrations" existed of basic text/csv exports from some of our applications or emailed reports. This process was very manual, and now the data just appears in our Data Lake and, all the changes are handled beautifully.
- In SAP, some tables are very difficult sometimes, impossible to ingest without major development/integration efforts, such as ingesting pool/cluster tables. The method we have previously used in going via the SAP API (RFC) has also been much slower, and managing the data changes has had to be managed programmatically
- We will be able to ingest data from some applications at a higher frequency than daily/nightly, which helps with the number of use cases we often have to deal with around manufacturing processes
- In SAP, some tables are very difficult sometimes, impossible to ingest without major development/integration efforts, such as ingesting pool/cluster tables. The method we have previously used in going via the SAP API (RFC) has also been much slower, and managing the data changes has had to be managed programmatically
- We will be able to ingest data from some applications at a higher frequency than daily/nightly, which helps with the number of use cases we often have to deal with around manufacturing processes
Easy set up, excelent customer service and helps us save a lot of time in our analysis.
What do you like best about the product?
The easiness to set up connector with different platforms and the accuracy of the data. If there was a problem, the customer service people tend to help out right away.
What do you dislike about the product?
Would be good to get a projected MAR usage and cost based on the changes you make in the in-between months. As currently, it only shows i'm projectd to spend $300 by in fact it would be way under $150.
What problems is the product solving and how is that benefiting you?
Building custom tables of daily KPIs from different platforms.
As a consultancy, we save a lot of time gathering data from different platforms and analysing with Fivetran compared to the traditional way.
As a consultancy, we save a lot of time gathering data from different platforms and analysing with Fivetran compared to the traditional way.
Great bootstrapping option for the Modern Data Warehouse, but still some way to go
What do you like best about the product?
As the title suggests it's a great option for bootstrapping a brand-new data department where Data Engineers are expensive or difficult to hire. It works well with other lean-team modern data warehouse-type technologies such as Snowflake and DBT. I got 850 Shopify tables and a few other AD sources setup really quickly
What do you dislike about the product?
Whilst Fivetran runs interchangeably across data warehouses,
1) There lack support for low-latency refresh which means if you need data in your apps or dashboards within 5-10 minutes you'll need to build your own custom pipeline
2) APIs are interpreted and landed nicely for you, but this also means there will be a huge switching cost once you build your pipeline on top of the Fivetran loaders.
3) More complicated or large connectors just don't live up to the low-fuss no-code philosophy. There isn't enough architectural knowledge on the Fivetran team to help deploy these connectors successfully.
4) Their logging could be better, troubleshooting really complicated issues like wrong writes has been a non-starter since no write logs take place we simply can't tell how a wrong write ended up there
5) Primary Tables work great (tables with updated timestamps), but not everything syncs and we often have missing records on secondary tables - these are REALLY hard to verify (you only find out when the business points it out)
Some Examples of 3:
1) E.g. We've tried to set up a NetSuite connector for over 6 months, the lack of an ERD or data-dictionary map just makes it really tough to get it going
2) Google/Facebook Ads ==> Some connectors don't really drop data as expected - for web marketing you end up receiving jinja variables rather than the actual attribute {{ UTM }}, other tools such as Supermetrics tend to do better in imputing these for the end user.
1) There lack support for low-latency refresh which means if you need data in your apps or dashboards within 5-10 minutes you'll need to build your own custom pipeline
2) APIs are interpreted and landed nicely for you, but this also means there will be a huge switching cost once you build your pipeline on top of the Fivetran loaders.
3) More complicated or large connectors just don't live up to the low-fuss no-code philosophy. There isn't enough architectural knowledge on the Fivetran team to help deploy these connectors successfully.
4) Their logging could be better, troubleshooting really complicated issues like wrong writes has been a non-starter since no write logs take place we simply can't tell how a wrong write ended up there
5) Primary Tables work great (tables with updated timestamps), but not everything syncs and we often have missing records on secondary tables - these are REALLY hard to verify (you only find out when the business points it out)
Some Examples of 3:
1) E.g. We've tried to set up a NetSuite connector for over 6 months, the lack of an ERD or data-dictionary map just makes it really tough to get it going
2) Google/Facebook Ads ==> Some connectors don't really drop data as expected - for web marketing you end up receiving jinja variables rather than the actual attribute {{ UTM }}, other tools such as Supermetrics tend to do better in imputing these for the end user.
What problems is the product solving and how is that benefiting you?
Bootstrapping - As the person leading up a newly formed team, there was literally no way to build a Data Warehouse within 6 months without one of these low-code points and click connectors. I had a look at Stitch vs. Fivetran and decided to go with Fivetran even though Stitch had more connectors because Fivetran had developed DBT packages. Even though I no longer use them (the packages), they were a huge timesaver when I first started out.
Great Low/No Code ETL and takes the headache out of large, regular data lift and shifts
What do you like best about the product?
Easy to use. Quick to get in place. Lots of support for applications and standard connections
What do you dislike about the product?
Can become expensive for data heavy integrations which potentially are still easy or much cheaper with other solutions which means you end up with multiple ETL tools
What problems is the product solving and how is that benefiting you?
Their out of the box connector saved a huge amount of work getting data out of an enterprise platform and across to our data warehouse.
Good software but expensive compared to competitor like stitch
What do you like best about the product?
quality product, more solid than competitor's product
What do you dislike about the product?
price, much much more expensive, and force customers to sync unnecessary tables that drives up the cost. stitch is much, much, cheaper when it works.
What problems is the product solving and how is that benefiting you?
sourcing data from various saas software without me handling all the api calls
Fivetran helped my startup get control of our data
What do you like best about the product?
Fivetran offers a wide selection of pre-packaged connectors that covers the majority of use cases but also allows users to leverage the power of custom functions (e.g Azure Functions) in order to create their custom connectors
What do you dislike about the product?
Oftentimes the user interface is a little slow to respond or does not instantly update. I also wish I could be given more advanced options on how to manage "broken" connectors.
What problems is the product solving and how is that benefiting you?
It allows me to connect new data sources to my warehouse and manage everything easily without having to maintain any data engineering infrastructure, all by using an intuitive UI. This benefits me by saving me time and taking away the need for a dedicated person in my team that would work on data engineering.
Easy setup
What do you like best about the product?
Amount of different integrations available with a couple of clicks and no additional coding required to get started. Particularly we were missing an integration like this for Chartmogul which doesn't seem to be so popular and found it here.
What do you dislike about the product?
It is kind of hard to understand what each item in the schema means, since the documentation may refer to something but not exactly what it means which makes it hard to know if that table is or not necessary for each specific use case. A glossary with more detail definition on what each table includes and what each thing means would expedite the onboarding process with each new connector.
What problems is the product solving and how is that benefiting you?
Almost real time syncing of different platforms to big query
Fivetran is great for SaaS use-cases
What do you like best about the product?
Ease of setup, schema management and error alerting
What do you dislike about the product?
Cost structure can be a pain for startups, especially at high volumes. Specific use cases do not make financial sense for smaller companies and tighter budgets.
What problems is the product solving and how is that benefiting you?
Quick ETL from our SaaS tools into our Database. It allowed our Analytics team to quickly become valuable rather than building custom pipelines for Salesforce and Asana.
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