@dyaffe Congrats on the launch, Real-time data gathering and Synchronising data between multiple sources are impressive features that could save us a lot fo time
@huy_doan_quang thanks! One difference is that Segment is a Customer Data Platform, whereas Flow is much more generic. We've tended to focus a bit more on integrations with things like databases, and Segment focuses more on things like capturing data directly from your website. We've actually had users push data from Segment into Flow (using webhooks) in order to materialize their data to an OLAP database like Bigquery or Snowflake.
One other difference is that Segment is more focused on point-to-point integrations, while Flow focuses more on "data products". When you "capture" data in Flow, you don't just have the ability to materialize it somewhere else. Flow captures data into "collections", which have all the features of data products:
- Discoverable: Users can come to Flow to find the data they need
- Governance: Flow's authorization system allows you to safely share data across users, teams, and even organizations
- Quality: Flow does schema validation at every step, and built-in transforms let you clean up your data and provide meaningful guarantees about the output data
- Observable: Flow automatically instruments every task in a pipeline so you can stay on top of what's happening. (note that we're still working on exposing some of these observability features in the UI)
@huy_doan_quang Just to piggyback on Phil's answer: a fun thing you can do with Flow is capture WebHooks coming from Segment to then use for your own purposes.
- Flow them into an analytics warehouse like Snowflake or BigQuery.
- Roll them up into a live dashboard kept in a Google Sheets.
- Transform and aggregate your Segment events into a customer 360 profile.
@johnny_graettinger1 wow, it sounds super cool. Thank you for the explanation guys! Keep it up! Also, is Estuary Flow on Twitter? Would love to see and catch up with your product updates in the next few weeks/months.
@gurudeep_shrotriya Hello Gurudeep, thank you for your kind words!
Estuary Flow serves the purpose when you want to move data from APIs, databases, or different technologies, to certain destinations. On the way, you can define real-time transformations. All of this happens in real-time so you get milliseconds latency between changes in your source database and your destination. If you have a certain problem that you are trying to solve, we would be more than happy to discuss it as well.
A few use cases that come to mind:
1. Gathering your analytics from different SaaS that you use (e.g. HubSpot, Salesforce, Mailchimp, etc.) and consolidating them in a single destination for analysis (e.g. Snowflake)
2. Synchronising data between a database and an Elasticsearch cluster, to allow for your data to be searched on
3. Synchronising data between SQL and/or NoSQL databases, e.g. if you are migrating from one database to another and want to keep data synchronised between the two, or for any reason you have specific use cases for different databases. e.g. Move data from Firestore to Postgres or MySQL to MongoDB, etc.
4. Sending events to a queue technology (e.g. Google PubSub) when certain changes are made to your data in any source
5. [... The list goes on!]
@gurudeep_shrotriya@mahdi_dibaiee and another very common one is just doing change data capture from databases to warehouses! If you use streaming sql to create a materialized view, it can save a good amount of money when you query that warehouse.
Hey, great launch!
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Congrats David on creating Estuary Flow! π It's an awesome real-time data platform with great features. Have you considered adding more capture options? That would be really useful. Thanks for providing a free plan, looking forward to exploring more! π
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