We have multiple data available from multiple sources. We use the tool to collect the data in one data warehouse.
Fivetran Data Movement Platform
FivetranExternal reviews
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Excellent reverse ETL and data pipelines tool
What do you like best about the product?
Census interface makes it easy to connect two platforms, since the implementation and day to day usage were quite simple. Also, it has error detection capabilities that I haven't seen in other solutions. It also seems to have a very robust connection engines, since I seldomly experienced downtimes. That way, you don't have to necessarily keep an eye on it at all times and can be logged out of the admin platform for days.
What do you dislike about the product?
Census' principal downside is its price, since it can be quite steep for medium-to-small companies. It also lacks some on-the-fly transformations functionality, at least on the tier I was registered to.
What problems is the product solving and how is that benefiting you?
Used Census to ingest Hubspot data to different cloud platforms, and then feed it back to Hubspot in some capacity.
Absolutely seamless data pipeline automation solution with an interesting pricing model
What do you like best about the product?
The solution is absolutely intuitive and works seamlessly. It has scheduled maintenances from time-to-time, but nothing that obstructs daily business. The connectors have a very easy set-up and sync process. The pricing model also seems to be pretty reasonable if you are using the solution to connect multiple data sources, but with low-mid volume of data.
What do you dislike about the product?
The number of connectors are a bit limited and their custom connector creation is completely on you and is not really user-friendly. Also, a lot of connectors only have a full sync of all possible data you have on a source system and not selective sync that enables you take only the required data to your destination. This leads to unnecessary data being dumped on to your destination and incurs more costs to the client.
What problems is the product solving and how is that benefiting you?
Fivetran enables us connect multiple data sources and siloed systems with very less effort and that helps us focus on driving business outcomes rather than focussing on ETL and creating data pipelines. Fivetran also helps us connect to systems that have no direct connection to our visualization tools like Power BI or Tableau.
Census Review: Excelling in Data Integration and Ease-of-Use
What do you like best about the product?
What I appreciate most about Census is its remarkable capability to eliminate the need for extensive coding when pushing data into various system APIs. As someone managing both data engineering and data analytics teams, I recognize the immense value this brings. It not only saves a significant amount of time but also reduces the ongoing maintenance burden associated with custom code. This feature allows our teams to focus more on strategic data analysis and less on the technical intricacies of data integration. Census effectively bridges the gap between complex data operations and user-friendly functionality, making it an indispensable tool in our data management toolkit.
What do you dislike about the product?
While Census excels in many aspects, one area that could be enhanced is the control and customization of alerts. In our operation, where timely and accurate data flow is crucial, having the ability to direct specific pipeline alerts to designated Slack channels would significantly improve our response efficiency. Currently, the alerting system in Census, though effective, lacks this level of granularity. This means that alerts from various pipelines may not be as targeted as we would like. Being able to customize alert destinations based on the pipeline or data event would allow for more streamlined and focused communication within our teams. This feature would not only aid in quicker issue resolution but also help in maintaining an organized and efficient workflow, especially in a fast-paced data management environment.
What problems is the product solving and how is that benefiting you?
Streamlining Reverse ETL Processes: The primary benefit of Census for us has been its ability to streamline the reverse ETL process, particularly in eliminating the need for custom coding for different data payloads. This has significantly reduced the time and resources typically spent on developing and maintaining bespoke integration scripts.
Enhancing Salesforce Integration: By using Census to push data from our data warehouse into Salesforce (SFDC), we have improved the accuracy and timeliness of our customer data. This seamless integration ensures that our sales and customer service teams have the most relevant and up-to-date information at their fingertips, enhancing customer relationship management.
Identifying Customer Expansion Opportunities: Census plays a crucial role in our customer expansion strategy. It helps us track and highlight when customers are utilizing beyond their provisioned quota. This insight enables us to proactively approach these customers with targeted expansion or upsell opportunities, thus driving revenue growth.
Enriching Data in Intercom and Amplitude: We also leverage Census to enrich our Intercom and Amplitude datasets with key business metrics. This enrichment allows us to have a more comprehensive view of our customer interactions and product usage, facilitating better-informed decisions and more personalized customer experiences.
In summary, Census is not just a tool for data integration; it's a catalyst for operational efficiency, strategic customer engagement, and data-driven decision-making in our organization. Its impact goes beyond mere technical functionality, playing a pivotal role in enhancing our overall business processes.
Enhancing Salesforce Integration: By using Census to push data from our data warehouse into Salesforce (SFDC), we have improved the accuracy and timeliness of our customer data. This seamless integration ensures that our sales and customer service teams have the most relevant and up-to-date information at their fingertips, enhancing customer relationship management.
Identifying Customer Expansion Opportunities: Census plays a crucial role in our customer expansion strategy. It helps us track and highlight when customers are utilizing beyond their provisioned quota. This insight enables us to proactively approach these customers with targeted expansion or upsell opportunities, thus driving revenue growth.
Enriching Data in Intercom and Amplitude: We also leverage Census to enrich our Intercom and Amplitude datasets with key business metrics. This enrichment allows us to have a more comprehensive view of our customer interactions and product usage, facilitating better-informed decisions and more personalized customer experiences.
In summary, Census is not just a tool for data integration; it's a catalyst for operational efficiency, strategic customer engagement, and data-driven decision-making in our organization. Its impact goes beyond mere technical functionality, playing a pivotal role in enhancing our overall business processes.
Census help us to keep the data in sync
What do you like best about the product?
The best thing about Census is how easy configure it. Also, the tool helps us to get notified if we have an issue during the sync phase.
What do you dislike about the product?
Probably add more notification data source capabilities such as Slack.
What problems is the product solving and how is that benefiting you?
Keep in sync data in several datasources
Using Census at Apollo in my Growth Ops role
What do you like best about the product?
We utilize Census' reverse ETL to move data from our data warehouse into Apollo utilizing custom field mapping and it helps us run sequences and plays as part of our GTM strategy.
What do you dislike about the product?
Nothing of note. They've been very supportive in troubleshooting along the way.
What problems is the product solving and how is that benefiting you?
Moving data from point A to B
Pricing structure makes it nearly impossible to cost and resell
What do you like best about the product?
consistent schema and data syncing if running
What do you dislike about the product?
pricing model and costs based on sync efficiency vs actual data useage
What problems is the product solving and how is that benefiting you?
consistently updating multiple data sources into a data warehouse. great concept and simplifies an important part of the process
Product is good, sale team and price is terrible
What do you like best about the product?
Reduce remarkably time to insight / market of data products.
Reduce engineering part of data projects.
Reduce engineering part of data projects.
What do you dislike about the product?
Slow response on incidents, we used to got more than 2 weeks downtime of Facebook pages connectors and Fivetran refused all responsibilities.
They mostly stop supportive response after signing anual contract.
They mostly stop supportive response after signing anual contract.
What problems is the product solving and how is that benefiting you?
Pre-built connectors help us to push up the data extraction process
The product is affordable and easy to deploy, but the technical support must be improved
What is our primary use case?
What is most valuable?
The product has some seamless connectors, which are readily available.
What needs improvement?
The connectors from some websites are not available. It is hard to get the data and work on it. The product should expose the APIs in a better way. The cloud functions are very code-centric. A low-code tool or a no-code tool would give us more flexibility. The environment must be more development-friendly.
For how long have I used the solution?
I have been using the solution for two to three months.
What do I think about the stability of the solution?
The tool’s stability is good.
What do I think about the scalability of the solution?
Five people use the solution in our organization. We need two people to maintain the tool.
How are customer service and support?
The technical support must be improved. There are a lot of communication barriers. We raise a ticket and wait for days. The team has integrations with communication channels, like Slack, but we have to wait for the support team to look up the issue and answer. The team was proactive during the proof of concept, but the support got slower as soon as we got the license.
How would you rate customer service and support?
Neutral
How was the initial setup?
The product is cloud-based. The deployment process is very straightforward. We get the data from different websites and integrate it into our database. We just sync the data on a daily or weekly basis. We needed two people for the deployment. It took two to three days to deploy the tool.
What's my experience with pricing, setup cost, and licensing?
The solution is affordable. The pricing model is good.
Which other solutions did I evaluate?
We evaluated Domo, Snowflake, and Airbyte. We chose Fivetran because it was a prominent product in the market.
What other advice do I have?
I did the proof of concept, and my organization is in the process of deploying the solution. We have a lot of issues. People who want to work with the product must list the requirements of the extraction website and the web sources from which the data needs to be extracted. They should choose Fivetran only if the connector is readily available. They must not search for custom connectors. Overall, I rate the tool a seven out of ten.
Fivetran has been a valuable addition to our data tools arsenal
What do you like best about the product?
Fivetren makes data processes simple/quick. Our team likes how easy it is to start without any coding. There are many turn-key connectors available, which is great for businesses that we provide IT services for. Also, their netsuite connector helps us move data smoothly. The interface is quite user-friendly, so we can delegate tasks to junior data specialists within our tema and cut maintenance costs for our clients.
What do you dislike about the product?
A recurring concern is the pricing model, particularly the cost associated with automating and tracking historical data and data warehouse tables. The model based on monthly active rows can be confusing, making it challenging to forecast expenses, especially for our enterprise customers with vast amounts of data.
What problems is the product solving and how is that benefiting you?
We use Fivetran as one of the key elements of our client's data systems. It assists with ELT, offers out-of-the-box integrations for most of the common SaaS tools our clients use, and then the data goes straight to the warehouse. We also created three custom connectors ourselves. Everything works pretty smoothly and requires little attention for maintenance.
Easy to learn, so you can quickly manage ETL pipelines, but it could have more customization options
What is our primary use case?
We mainly use Fivetran for ETL.
What is most valuable?
There's a very good layer that allows you to connect different data sources and establish a very good ETL workflow. You can manage all of your connectors individually, which gives you a very good ability to trace which one of your ETL processes is running and when. The solution also allows you to schedule each of those runs with different cadences, depending on which plan you are on. At the same time, for those runs, you have the ability to hash, unhash, or map any data that might be sensitive or personally identifiable, and that's pretty robust. It's a feature in the standard plan, so you don't need the enterprise plan for that. One very powerful and cool feature is how you can integrate the solution with other transformation tools, such as dbt, or run the transformations within Fivetran itself to create a transformation layer on top of your ETL layer. That allows you to manage the entire ETL workflow end to end from within the platform without the need for any additional tool.
When it comes to managing ETL pipelines, these features are valuable.
What needs improvement?
Given that Fivetran is a fully managed third-party solution, the customization could improve because Fivetran gives more thought to people who don't want to manage analytics workflows rather than engineers who want to be able to customize pipelines more thoroughly.
For how long have I used the solution?
I've had experience with Fivetran for about two-and-a-half to three years.
What do I think about the scalability of the solution?
The scalability will directly relate to the plan you're on. It will be very important to see that the provisioning in compute and the provisioning you have to run workflows and jobs will also be directly related to your use case. Managing scalability in that way is a bit complex, but you get a lot of support from Fivetran.
How are customer service and support?
From a customer support standpoint, Fivetran does an amazing job in establishing and helping you customize while ensuring you have the right plan for your data needs. I have full contact with our account executive, and she's super nice and walks us through many of these use cases that will be important in the future and many of the estimations we might need for the workflow we plan on integrating.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I have used Splunk before, and it's more technical. Splunk allows you to version things and have a good engineering process around your ETL pipeline. It also has very good logging and documentation tools. But now that Fivetran has a better exposed API, it is much more flexible. But Splunk beats Fivetran regarding things like customization, for example. We switched to Fivetran because we reduced the engineering team. We had fewer people to manage all the different ETL processes, so we had to leverage more automated third-party tools, and Fivetran made onboarding new engineers a lot easier.
How was the initial setup?
Fivetran is very easy to set up. It's a matter of having the connection information of each one of the endpoints you want the ETL through. The solution is very comprehensive and easy to set up. It even gives you assistance on where to find the information that you might need, depending on the data source. It has pre-built connectors for the most common data sources, so it also helps you expedite that process if you are not super tech-savvy.
What's my experience with pricing, setup cost, and licensing?
Fivetran has a pricing model that scales the more data sources you add. When you have a lot of workflows and complex use cases, pricing goes down as you use it more. That's a very good feature of its pricing. Fivetran might be a bit pricey for a very limited or small number of data sources that might be easily collected in other forms. The pricing gets better the bigger you are.
Which other solutions did I evaluate?
Comparing Fivetran to other tools such as dbt, AWS Glue, or Azure Data Factory, the other tools are more robust and allow us to run custom transformations.
What other advice do I have?
To anyone who uses the product, I say monitor. You have a dashboard to monitor your MAR, which is a row-level metric Fivetran uses to gauge how much you are consuming. If you can monitor your MAR closely, you can get a very good understanding of how much data you're moving, and it will allow you to adjust the cadences you might need to get a better bang for your buck. Watch your numbers and try to plug in as many data sources as you need because that will help you with pricing.
I rate Fivetran a seven or a seven-point five out of ten. It's solid and offers a very simple UI and way to get set up. It might fall short for people who want more advanced use cases or people who have knowledge and tools that they can integrate, and that's where things get a bit more technical. But I feel the leap from just getting started with it to getting very technical with it is very large. There's no middle ground.
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