Artlist deploys a complete data analytics infrastructure 4X faster


faster time to value (from 20% to 80% of data team’s time saved on engineering)

Instant data model access

company-wide (on an hourly and daily basis)


increase in analysts’ capacity to answer key business questions








Artlist is a leading creative technology company created by filmmakers for filmmakers. With original, high-quality music, SFX and footage, Artlist has revolutionized the industry becoming the go-to licensing provider for content creators in 160+ countries. Artlist clients include Google, Apple, Nike, Coca-Cola, Ikea, Mercedes, Samsung, Wix, Netflix, Dior and many more. 

Rivery is a no-brainer for anyone who wants to save significant time and money. If I had to describe Rivery in one word it would be simplicity. Rivery is quick to master and it requires very little onboarding. It removed our dependency of getting data from R&D. At the connection level, it gives very fast time to value and saves us huge costs.

Hannan Kravitz , Data Engineering Team Leader, Artlist


Artlist is a fast-growing company with a subscription-based product. Their data team works in sprints and needs to move fast to consume and pull data from sources like Bing Ads, Google Ads, LinkedIn Ads, Facebook Ads, Salesforce, PayPal, Stripe, BlueSnap, YouTube and TikTok to name a few and targets like Snowflake for campaigns 360 analysis. They also need to consume R&D data to understand product usage.

Artlist had trouble utilizing a two-person data team and their existing data infrastructure to build end-to-end data pipelines. This meant their R&D team was bogged down with subscription data management instead of important dev work. Artlist was seriously struggling and needed a solution to help them deliver fast business insights across the board. Even when the pipelines were created, the lean team was challenged with providing the analyst teams with visibility into data flows and helping them gain a better understanding of the data they work with. As a result, the supply of data was not meeting the rigorous demands of a product-led growth environment.

At Artlist, we move fast and work in sprints. We need to consume data from R&D to understand our product usage and make better decisions . We also need to enable our marketing team with actionable insights as quickly as possible.


If we create a campaign, we want to see if it’s working three hours in and get all those important funnel and conversion metrics right away. We need tools that are easy to implement and can scale fast enough to meet our growing demands.


It turned out Rivery, Snowflake and Aggua were the answer to Artlist’s various data needs and challenges. From the get-go Rivery and Snowflake provided significant value in terms of fast data delivery and time to market. From the get-go, Rivery provided significant value in terms of fast data delivery and time to market. 

The first challenge Rivery helped solve was at the connection and data modeling level. It replaced data silos with end-to-end data pipeline creation. Rivery’s simple setup, native connectors and ready-made data model templates make it easy to collect information from Facebook, Google Ads, BlueSnap, PayPal and others marketing apps and load the data into Snowflake tables and sub-destinations like Tableau, enabling product usage and marketing data to be consumed on an hourly basis by different teams every single day. 

The ability to connect to lots of data sources is a huge advantage for us. On a company-wide level if someone wants to integrate a source, Rivery’s native connectors and built-in data model made ELT deployment so easy.  Hannan Kravitz , Data Engineering Team Leader, Artlist

The second challenge resolved was on the data lineage and analysis level. To enable analysts to understand what data is coming through when they consume it in Tableau, Artlist leverages Aggua, a Rivery technology partner.  Aggua has a native integration with Rivery, where it pulls metadata via Rivery’s API in order to visualize data lineage. Along with Rivery’s metadata, an interactive interface allows analysts to explore the data lineage all the way from Tableau and Snowflake down to the original source and perform rapid impact analysis. 


Aggua makes data discovery and onboarding easy. It provides a single place where I can answer questions about my data from the source, through Rivery and all the way down to Snowflake and Tableau  Liat Ashkenazi, Head of Data, Artlist

As the data culture matured at Artlist and the data analytics infrastructure grew, the data engineering team scaled in size and started to tackle additional use cases. This growth triggered the need to handle additional integration with other processes orchestrated using Airflow. Here again, Rivery’s API came into play, this time used by the Artlist data engineering team to trigger Rivery workflows from Airflow. 

When it comes to operational databases, I can now run queries from marketing channels plus process analysis over the so-called unprocessed R&D data. Being able to embed all those queries on top of the data brought to our target warehouse, Snowflake has seriously boosted our productivity. 


It makes us 10X more productive. We now understand our data models better and we extract insights like conversion, funnel, spend metrics and other business insights that simply didn’t exist before. This ability is so valuable. It lets our marketing team focus their efforts really where they need to and that’s a huge money and resource-saver.



60% boost in time to value
Key metrics can now be tracked and analyzed, driving strategic decision-making
70% increase
in analysts’ capacity to answer key business questions
50% of R&D time freed up
Shift in roles and responsibilities has replaced manual data processing with pivotal dev work
5X bigger data team
(from 2 to 10 FTE) as a result of the increased appetite to use data everywhere for better decision-making and data ownership transferred from R&D to the data team
Significant resources saved with little to no onboarding for new data team members

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