4 Alternatives to Fivetran: The Evolving Dynamics of the ETL & ELT Tool Market
The ETL & ELT tool market is experiencing continuous transformation, propelled by fluctuating pricing structures and the advent of inventive alternatives. This industry remains fiercely competitive due to these changing elements and a swiftly growing user base. In the following sections, we will explore four emerging alternatives to Fivetran.
Of course, that is if you believe we should be using no-code solutions in the first place.
But for those who do, you are likely digging into possible alternatives to the current norm, at least when some of the solutions become too expensive, there are options. Many of which often work well in conjunction with Fivetran. In fact, in many situations, when it comes to implementing solutions for clients I may use one of these solutions along with Fivetran, not as an alternative, but to fill in any of the missing gaps or improve the overall cost of the solution.
But before diving into Fivetran alternatives, I do believe it’d be best to first talk about what Fivetran is and why it is so popular.
What Is Fivetran
Fivetran is a highly comprehensive ELT tool that allows end-users to easily move data from data sources to data warehouses like Snowflake.
Why Are Companies Turning To Fivetran?
As more third-party tools provide access to their data sources, companies are looking to build more and more data pipelines that get data into their data warehouses and data lakes.
Therein lies a major problem.
Data engineers, the ones responsible for building those pipelines are often the bottleneck.
Between having to build and deploy multiple new pipelines, building new datasets, and the constant one-off requests to add new columns. All of these requests start to quickly weigh down any data engineer team.
One option is to continually hire new data engineers. However, this is a very expensive endeavor. A data engineer can easily cost a company upwards of 100k per year. That’s a large extra expense to take on.
So that’s why Fivetran and other ELT tools have become popular.
Fivetran offers companies an automated data pipeline solution that simplifies the process of extracting, transforming, and loading data from a wide range of sources into a central destination. With pre-built connectors and support for real-time or scheduled data syncing, Fivetran ensures data accuracy, reliability, and up-to-date insights. Its easy setup, minimal maintenance, scalability, and focus on data analysis allow businesses to concentrate on deriving valuable insights from their data.
But Fivetran is far from the only option.
4 Fivetran Alternatives
So if you’re looking for an alternative to Fivetran, I’d also consider asking whether you need a replacement or an augmentation.
Regardless, here are four other EL(T) solutions you can use in your data stack.
Portable.io
One data connector solution that has been developed over the past few years is Portable.io. Porable.io is a cloud-based data integration tool that replicates data to Snowflake, BigQuery, Amazon Redshift, PostgreSQL, etc. What I have enjoyed about Portable is that it takes care of many of the long-tail data connectors that Fivetran doesn’t.
All for a flat fee.
Portable pricing
- Free Tier – This is only for manual syncs(so you better get used to clicking)
- One Off Scheduled data flow: $200/data flow with unlimited sources, destinations, and volumes
- Business Tier data flow: $1000 for up to 10 data flows
- Custom: For specific needs
Portable Features
- 500+ data source connectors
- Support for major cloud data warehouse providers
- Unlimited data sources, destinations, and volumes
- Free development and maintenance of new data integrations
- Hands-on support
What Stands Out About Portable
One of the reasons I enjoy working with Portable is that any time I needed a custom connector, I would email their support team, and they’d work with me to develop, test and productionize it.
All at no cost to me!
Basically, it is like having an extra engineer on my team.
Pros
- A flat pricing model, meaning you know what you’re paying upfront
- Try all connectors for as long as you want with no charge
- 500+ long-tail connectors that other ETL solutions don’t support
- Custom connector creation and support at no additional cost
Cons
- Doesn’t yet support the largest enterprise data sources (think Salesforce, thus using Portable in conjunction with other solutions makes sense)
- Doesn’t focus on databases as sources
- Not available internationally
Portable.io is a growing contender in this space with a readily accessible team, the CEO of Portable.io is frequently active on data engineering Reddits answering an array of questions.
But let’s talk about a solution that can also manage your real-time needs.
Estuary.dev
Estuary is a cutting-edge platform designed to revolutionize the way businesses handle their data pipelines. This innovative solution offers a no-code approach to building reliable pipes that don’t require scheduling, supporting both batch/streaming and materialized views in milliseconds. The platform is built on an open-source streaming framework called Gazette, which combines millisecond-latency pub/sub with native persistence to cloud storage, essentially creating a real-time data lake.
One of the standout features of Estuary Flow is its approach to data storage. When a data source is captured, the data is stored in your cloud storage as regular JSON files. This allows you to materialize all of that history and ongoing updates into a variety of different data systems, creating identical, up-to-date views of your data in multiple places, now or in the future. This feature, known as “Collections instead of Buffers”, provides a significant advantage over traditional data pipeline solutions.
Estuary offers “Turnkey batch and streaming connectors”, supporting both real-time and historical data through one tool and providing access to pre-built connectors to approximately 50 endpoints. You can also plug in your own connector through Flow’s open protocol, offering a high degree of flexibility.
The platform also offers schema validation and first-class support for testing transformations, with continuous integration whenever you make changes.
Finally, Estuary Flow provides “Managed CDC”, a simple, efficient change data capture from databases with minimal impact and latency. It also offers seamless backfills and real-time streaming out of the box, making it a comprehensive solution for data management.
Estuary pricing
- Open source: Completely free, as you manage the infrastructure yourself
- Cloud: $2.50/credit (one million rows = 6 credits; 1 GB = 4 credits)
- Cloud high volume: Custom pricing for those that need more than 5,000 credits
Estuary Features
- 75+ data source connectors (not all available on cloud service)
- Change data capture support for databases
- Support for data warehouses and data lakes as destinations
- Data volume-based pricing
What Stands Out About Estuary
Overall, Estuary makes moving large amounts of data fast and affordable. Most other solutions I looked into would often cost 2x-10x as much or would require me to code everything from scratch. Estuary helped me deliver data quickly into several customers’ data warehouses without having to spend time setting and managing multiple solutions to stream data.
Pros
- Robust coverage of high-scale technology systems, like databases.
- Data transformation with built-in testing
- Real-time data capture and processing.
Cons
- Estuary is a newer solution, so it is in a period of rapid change.
- Not as many SaaS integrations as some alternatives(this can be supplemented with Portable or Fivetran.
Estuary is a comprehensive solution for businesses looking to streamline their data pipelines. With its innovative features and commitment to continuous improvement, it’s a platform worth considering for any business dealing with large volumes of data.
Airbyte
Airbyte, an open-source project founded in 2020, has been making waves in the ETL & ELT tool market. This rapidly growing project has amassed 15,000+ community members, 11,000+ GitHub stars, and 3,500+ daily active companies. Their recent Series B funding round of $150 million has catapulted their valuation above $1 billion.
One of Airbyte’s standout features is its extensive range of connectors. Airbyte’s catalog of 350+ pre-built, no-code connectors(although I would poke and point out that many constantly have the Alpha tag) is the largest in the industry and is growing every year, thanks to its open-source community.
Airbyte also offers a built-in scheduler that can be orchestrated via the API with tools like Airflow, Mage, or Prefect. The platform was built with the concept of letting dbt take care of the small transformation step to normalize data, dropping raw data into your data warehouse or data lake, and then applying a basic normalization with a dbt script.
Airbyte pricing
- Open source: Completely free, as you manage the infrastructure yourself
- Cloud: $2.50/credit (one million rows = 6 credits; 1 GB = 4 credits)
- Cloud high volume: Custom pricing for those that need more than 5,000 credits
Airbyte Features
- 350+ data source connectors (not all available on cloud service)
- Open-source solution with direct access to code
- Change data capture support for databases
- Support for data warehouses and data lakes as destinations
- Credit-based pricing model or free option with self-hosting
- Warehouse-native data transformation
What Stands Out About Airbyte
I believe the biggest pro that Airbyte has going for it is its open source. This naturally attracts users to it as it allows them to spin up Airbyte instances internally. This is very important for some companies that might have more complex security and compliance needs.
Pros
- The open-source platform you can deploy on your own
- Engineer-focused platform with a CDK to speed up development
- Support for 20 destinations, more than many competitors including Fivetran
Cons
- You’ll need to develop and maintain long-tail connectors yourself
- Credit-based pricing model can be hard to predict
- Cloud service missing several popular connectors and destinations (e.g., WordPress, Google Analytics 4, Apache Kafka)
In conclusion, Airbyte is a promising, rapidly growing, open-source alternative to its Fivetran counterpart. With its extensive range of features and growing community, it’s a platform worth considering for businesses looking to streamline their data management processes.
Matillion
Proponents of Matillion’s ELT solution feel like it often surpasses Fivetran as it does far more than just EL. Unlike Fivetran which doesn’t have fully fleshed out transform capabilities and really just relies on DBT to perform its transforms, Matillion provides the end-user post-load transformations. Users can create transformation components with a very easy to interact with point and click UI. This can be very favorable for some companies that are looking to have a more all-in-one tool in terms of ELT.
Overall, Matillion can be a solid replacement.
Matillion pricing
- Free: Up to one million rows/month
- Basic: $2.00/credit
- Advanced: $2.50/credit
- Enterprise: $2.70/credit
Matillion Features
- 125+ data source connectors
- On-premises and cloud deployment options
- Cloud data transformation is presented with a graphic user interface (GUI)
- Supports ETL, reverse ETL, CDC, and several other forms of data workflows
Pros
- Strong data transformation capabilities built-in
- On-premises option available
- Since Matillion offers loading and transformation, it can be easier to implement data governance
Cons
- Matillion’s GUI-based transformations can have a learning curve
- Fewer data connections than other competitors, including Fivetran
Which Solution Works Best For You?
ELT solution has to mesh with the technique and strategy involved in the company’s processes. The ELT platform can as mentioned, save coding hours, but it needs to be integrated the right way to provide the best service. That means understanding where data will be deployed at the endpoint and figuring out all of the primary sources that are priorities for centralizing data.
Any of the above resources can work with the right implementation and design. By taking on more of the data center process in an automated and replicating way, the company is easing the burden on its in-house staff and positioning for better scalability and growth. Take a look at some of the top ELT tools, to understand how these are integrated into a commercial context, and what that means in the age of the cloud and SaaS.
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