Power Your Real-Time Analytics Without The Headache Using Fivetran's Change Data Capture Integrations
Data Engineering Podcast
00:00
Five Trac Data Capture Platform
In terms of the way that five tran has been doing business, where it's largely been bach oriented from a source to a destination. Some of those technologies aren't necessarily suitable for sub second kind of latency. We're not quite there yet, but this is absolutely part of our journey as we integrate those acknowleges for change data capture. And i think if you look at the number li like some of the most popular data destinations, whether that is snowflake or data bricks,.
Transcript
Play full episode
Transcript
Episode notes
Summary
Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. The team at Fivetran have recently introduced that functionality to power real-time data products. In this episode Mark Van de Wiel explains how they integrated CDC functionality into their existing product, discusses the nuances of different approaches to change data capture from various sources.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
- When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show!
- You wake up to a Slack message from your CEO, who’s upset because the company’s revenue dashboard is broken. You’re told to fix it before this morning’s board meeting, which is just minutes away. Enter Metaplane, the industry’s only self-serve data observability tool. In just a few clicks, you identify the issue’s root cause, conduct an impact analysis—and save the day. Data leaders at Imperfect Foods, Drift, and Vendr love Metaplane because it helps them catch, investigate, and fix data quality issues before their stakeholders ever notice they exist. Setup takes 30 minutes. You can literally get up and running with Metaplane by the end of this podcast. Sign up for a free-forever plan at dataengineeringpodcast.com/metaplane, or try out their most advanced features with a 14-day free trial. Mention the podcast to get a free "In Data We Trust World Tour" t-shirt.
- RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder.
- Data teams are increasingly under pressure to deliver. According to a recent survey by Ascend.io, 95% in fact reported being at or over capacity. With 72% of data experts reporting demands on their team going up faster than they can hire, it’s no surprise they are increasingly turning to automation. In fact, while only 3.5% report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. 85%!!! That’s where our friends at Ascend.io come in. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP. Go to dataengineeringpodcast.com/ascend and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $5,000 when you become a customer.
- Your host is Tobias Macey and today I’m interviewing Mark Van de Wiel about Fivetran’s implementation of change data capture and the state of streaming data integration in the modern data stack
Interview
- Introduction
- How did you get involved in the area of data management?
- What are some of the notable changes/advancements at Fivetran in the last 3 years?
- How has the scale and scope of usage for real-time data changed in that time?
- What are some of the differences in usage for real-time CDC data vs. event streams that have been the driving force for a large amount of real-time data?
- What are some of the architectural shifts that are necessary in an organizations data platform to take advantage of CDC data streams?
- What are some of the shifts in e.g. cloud data warehouses that have happened/are happening to allow for ingestion and timely processing of these data feeds?
- What are some of the different ways that CDC is implemented in different source systems?
- What are some of the ways that CDC principles might start to bleed into e.g. APIs/SaaS systems to allow for more unified processing patterns across data sources?
- What are some of the architectural/design changes that you have had to make to provide CDC for your customers at Fivetran?
- What are the most interesting, innovative, or unexpected ways that you have seen CDC used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on CDC at Fivetran?
- When is CDC the wrong choice?
- What do you have planned for the future of CDC at Fivetran?
Contact Info
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
- Thank you for listening! Don’t forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
- Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
- If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
- To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers
Links
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
The AI-powered Podcast Player
Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
