Fivetran vs. Twilio Segment

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.

Incentivized

Best suited: - Merging emails coming from: Facebook leads forms, Unbounce or landing pages forms, Google forms, any other kind of lead generation tool and bundling all that information together for a single user "profile". - Passing events generated in multiple applications by the same user (product selected in web, product discarded in cart, etc) and delivering those events into other applications (like a CRM) Less appropriate: - Reading/updating data directly from segment from a frontend application

Incentivized

• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

Incentivized

• Multi-platform. Segment has easy integrations in many different web, backend, and app platforms/frameworks. We use the Segment SDK in Android and iOS as well as our node.js backend.
• Segment is fairly affordable for early-stage companies that are trying out different analytics software. The "developer" plan is free and is suitable for most companies with products that have a small user base.
• The UI is great! It is extremely intuitive and easy-to-learn, and this made it take very little time to integrate this software into our analytics and marketing workflows.

Incentivized

• More detailed logging
• More flexible choices for time range over which records are synced
• More options for masking and excluding sensitive data

Incentivized

• More and richer sources. For example, MailChimp is a source but the data you get from MailChimp is quite limited. I ended up writing my own scripts to take better advantage of MailChimp's API because Segment's integration was lacking.
• Better examples on how to set up event tracking. Pageview tracking is easy enough, but it would be nice if they had a sample app and corresponding code for it and showed you, via Git commits, how to add various kinds of events.

Incentivized

Just need to input connection info.

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

Incentivized

Over the period it took us to set up, we kept going back to their enablement team to help us with the setup, and they were always ready and were very helpful in the entire process. Even with their documentation, they took the time out to help us work through the process. We've never had a message/email unanswered for more than an hour on working days.

Incentivized

We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

Incentivized

I'm not sure these are "official competitors" (or alternatives) to Segment, but we use them in parallel for different goals. We use Datadog for logging and monitoring and we use Mixpanel to perform data analysis based on the data we gather using Segment (and other sources). I don't think we ever evaluated any other service vs. Segment. I think we got a recommendation on Segment, liked it and decided to use it (and we're happy with it since).

Incentivized

• Development cost have reduced for each connector
• The pay-per-use model is still not out their which requires lot of overhead cost

Incentivized

• Segment has enabled us to get a full view of our front end activity, join it to our back-end activity, and get full visibility into our funnels and user activity.
• Segment lets us send events to ad tools with a full audit trail so all the numbers line up.
• Segment also brings data from other sources into our data warehouse, saving our data engineering time from building commodity connectors.