Growth Rate (y/y)
Note: All data as per publicly available information
Fivetran made an estimated $83M in 2021, and we believe it will make $190M in 2022. It grew at a CAGR of 77% over the last two years. It has a hybrid pricing model with SaaS-style pricing tiers linked to consumption-linked billing. Customers pay for the number of rows of data edited or added to the data warehouse in a month, with higher-priced subscription tiers getting more users, features, and faster syncs. In 2021, it acquired HVR, whose $30M revenue got added to Fivetran’s 2021 revenue. It has 4000+ customers, including JetBlue, Forever 21, Condé Nast, and WeWork.
Note: All data as per publicly available information. Size of the bubble indicates valuation. Horizontal axis is in log scale for visual clarity.
Fivetran has raised $728M from investors such as Andreessen Horowitz, Matrix Partners, and General Catalyst. Its last private valuation was $5.6B, with a revenue multiple of 59x. Companies in the data integration segment have much lower revenue multiples, such as Informatica at 3.7x, Matillion at 26x, and Talend at 7.3x. Fivetran’s high revenue multiple reflects its 100% YoY growth and its wedge into the large enterprise market through HVR's acquisition. Modern data stack companies DBT Labs (280x) and Airbyte (1500x) have very high revenue multiples as investors are pouring money into startups commercializing open-source software after the success of Databricks.
Modern companies use multiple applications like Salesforce for CRM, Stripe for payments, Zendesk for customer support, and cloud databases that capture transactions like flight booking and payments from their websites and apps. To know what is happening in the business, they want to move all the data to a data warehouse where analysts can run queries and build dashboards. For this, the first step is to copy the data from these source systems (called Extraction) and replicate it in the data warehouse (called Loading).
Fivetran is a Plaid-like data pipeline tool that automates the grunt work of ‘extraction and loading’ by moving data from multiple applications and databases to a central data warehouse like Snowflake or BigQuery without any coding.
Before Fivetran, data engineers spent considerable time building these data pipelines by writing code manually. However, it is hard to build pipelines for every possible source application as each has a different schema, data types, and APIs. Also, these connectors got old fast as APIs often changed without notice, breaking the connectors and making the maintenance harder than building them.
Fivetran sells a library of 200+ fully-managed connectors that companies can use in a plug-and-play manner without using developers. It covers popular apps like Stripe, Google Analytics, Salesforce, and Shopify and longtail apps like SugarCRM and Reddit. It monitors all connectors for API changes, schema changes, downtime, etc., sending alerts to customers if any connector is down.
Its SaaS-style pricing converts the fixed cost of hiring expensive data engineers to build/maintain data pipelines to a variable monthly cost. As companies capture more data and send it to their data warehouses, Fivetran makes more money with its consumption-based pricing model. Thus, Fivetran grows with its faster-growing customers.
Fivetran found an initial product-market fit by selling to tech start-ups from its Y Combinator’s network, which were building apps on the cloud and couldn’t use the existing data integration software designed for on-premise data warehouses. By making it easy to send data from point A to point B, Fivetran freed their engineers from writing custom integration code to working on more critical tasks.
Fivetran’s core product is the data connectors library that pulls in data from source applications and replicates it into a data warehouse, monitors the connections, and alerts customers when something goes wrong. Its other data replication product, CDC database replication, is used to automate high-volume data movement, typically in the case of connections between Oracle and Snowflake or migration between cloud data warehouses.
Fivetran offers two types of transformations - basic SQL transformations and dbt Core, with additional features like version control, lineage graphs, and documentation. Customers use transformations to get their raw data into shape for downstream uses such as visualization or reverse ETL. Along with the connectors, the transformations give data teams control over the entire data pipeline without using data engineering resources.
Powered by Fivetran
By using Powered by Fivetran, companies give a web portal to their end customers for connecting their data sources to the Fivetran instance being run by the company. For instance, a marketing data company can publish a web application to a customer using which they can connect data sources like Google Ads and Google Analytics in a self-service way to Fivetran managed by the data company.
As more companies move their data warehouses to the cloud, legacy data integration companies built for on-prem data warehouses are playing catch-up with cloud-native data integration companies like Fivetran. These cloud-native data integration companies have similar features, making it hard to differentiate them. While data warehouses offering their own ELT pipelines are a threat to Fivetran, a bigger headwind is the bundling of data pipelines by large SaaS apps that can connect with any data warehouse.
Data integration companies
Informatica (market cap: $5.3B) is one of the largest data integration companies, which started with data connectors for on-prem data warehouses. It offers more features than Fivetran, like data quality management, data governance, and cataloging, which makes it appealing to enterprises but too complex for startups and mid-market companies. Another competitor, Airbyte ($1.5B), is taking an open-source community-based approach to sell at 10x cheaper than Fivetran and add 500 connectors in 2022.
SaaS companies like Segment, Salesforce, and Hubspot offer native connectors that sync data with Snowflake and other cloud data warehouses without using Fivetran. While it is unlikely that all the thousands of SaaS applications will offer such connectors due to the time and cost involved, we are seeing a trend of bigger SaaS companies moving in this direction. They can make more money by rolling it as a feature into their higher-priced tiers. Startups like Y Combinator-backed Prequel are selling out-of-box data connector solutions to SaaS companies taking away the pain of maintaining them. This is a key headwind for Fivetran as most of the data replication volume comes from a handful of SaaS applications. Once they provide native connectors, startups can write custom integrations for low-volume long-tail jobs without using Fivetran.
Cloud data warehouses
AWS Glue, GoogleData Fusion, and MicrosoftAzure Data Factory are native cloud data integration tools that work well when companies want to standardize their operations on a single cloud platform. However, CIOs/CDOs often worry about getting locked into a vendor and want to use different vendors across different data pipeline stages. As these tools are add-ons rather than core products for cloud providers, the UX is basic, with limited connectors compared to Fivetran.
HVR and Fivetran have different tech stacks, and it may take a long time to integrate HVR fully into Fivetran’s offering. This can delay Fivetran’s enterprise expansion, which is expected to be a major source of future growth
Native data connectors from SaaS companies
As SaaS companies add native data connectors to their offering, with the help of startups like Prequel, companies don’t need to use Fivetran for at least some of the latest SaaS apps. While this doesn't make Fivetran disappear, with its consumption-based pricing, Fivetran loses revenue as these large SaaS companies are the ones that create the most data.
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