Product News

Census + Databricks = OA | Census

Boris Jabes
Boris Jabes February 11, 2021

Boris is the CEO of Census. Previously, he was the CEO of Meldium, acquired by LogMeIn. He is an advisor and alumnus of Y Combinator. He enjoys nerding out about data and technology, 8-bit graphics, and helping other startup founders.

Since our public launch, Databricks has been one of the most requested data sources. That elusive fifth warehouse. And with their Delta lake product widely available, we knew this was something we wanted to integrate.

For those of you unfamiliar with Databricks, they are most famous for championing Apache Spark and making the old world of Hadoop-driven “big data” orders of magnitude easier & faster. As they’ve grown, they’ve added a number of offerings to their stack, all of which help move our industry from focusing on data processing towards AI & ML outcomes. In this regard, our missions are deeply aligned. The whole point of Census is to turn your warehouse (or shall I say "lakehouse") into an operational hub that helps you turn data into action.

So we’re excited today to announce our Databricks Delta Lake integration 🎉

Delta Lake brings a built-in storage layer for Spark, which expands the platform to match other cloud data warehouses like Snowflake & BigQuery but with the perk of having Spark running next to it to transform and process your data (e.g. transforming events into actionable attributes 😉).

With our new integration, you can connect your ML & analytics directly into every part of your business operations – not just your product, but your go-to-market teams in Salesforce, Marketo, Zendesk, Hubspot, and many more.

Here’s just a sample of the kinds of things our customers have been doing with Census that you can now do if you’re a Databricks user:

  • Build a lead scoring model based on the actions in your application and automatically route them sales reps at the right time.
  • Sync aggregated usage metrics & customer journey milestones into customer support tools to prioritize tickets on more than just revenue.
  • Detect drop in usage and alert the assigned customer success manager to prevent revenue churn
  • Remove engaged customers from high-cost advertising campaigns to optimize your ad spend.
  • … and many more use cases!

Getting Started

To get started, simply start your trial and connect your Databricks cluster!

We’re always happy to give you a personalized demo too. Just contact us.

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Sync data 100x faster on Snowflake with Census Live Syncs
Sync data 100x faster on Snowflake with Census Live Syncs

For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps: