Nexla Vs. Fivetran
Head-to-Head Comparison
Compare Nexla and Fivetran, and see the differences between the two platforms.
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Fivetran |
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| Overview | Data integration, transformation, delivery, observability, and monitoring for all data to anywhere | Managed ELT service to data warehouses |
| Connector Types | SaaS Apps, Warehouses, Lakes, Streaming, Webhooks, API, Databases, Files, Spreadsheets, and more | Saas Apps, Files, and Databases |
| Bulk/batch data movement | ELT, ETL, Streaming, API, API Proxy | ELT |
| Data movement topology | Bidirectional data flow with tunable latency and speed | One way ELT pipelines – from apps to data warehouse |
| Batch, Streaming, and Real-time Processing | Batch, Streaming, and Real-time | Batch only, then only native database change capture |
| API services | REST, SOAP, and Oauth connectors | Not as data connector |
| Data Mesh Architecture Principles | Data products (Nexsets), domain governance, metadata intelligence, and more | Not applicable |
Nexla and Fivetran can both be used to build direct replication ELT data pipelines, but Nexla is also built for all other data use cases such as ETL, Reverse ETL, Streaming, API, and more.
For a more fine-tuned control over every aspect of a data flow, Nexla provides the suite of features and tools businesses need. For more complicated flows that require custom transformations, branching, or specific configurations, Nexla enables anyone to build exactly the flow they need — while making data engineers’ jobs easier by automating the straightforward tasks.
Nexla sees ELT as just one aspect of complete data operations, and envisions a platform where anyone who works with data is enabled to build any flow they need in minutes rather than months.
Difference #1: ETL, ELT, Reverse ETL, Streaming, API, and Anything Else
Fivetran is for ETL mode data pipelines with a smaller set of connector types from major SaaS apps to database destinations. Nexla’s goal is to provide unlimited flexibility to build any and all of the flows a data-driven business might need, covering all ETL, ELT, Reverse ETL, Streaming, API, and other use cases. In addition, Nexla provides a suite of pre-built data transformations and all the custom transformations you need with custom Python, Javascript, or JSON for ETL and other modes of movement. Fivetran does not support user transformations.
Difference #2: Data Products
Nexla automatically detects, creates, manages, and organizes data products from all of your data sources and transformations. At scale, data products enable inter-team and cross-team collaboration with ease and make it easy to find and use exactly the right data anyone needs every time. Fivetran focuses mostly on ETL pipeline building, and therefore has no concept of data products.
Difference #3: Custom Transformations without DBT
While Nexla can trigger dbt transformations, Nexla also runs its own transformations, providing a suite of pre-built transformations as well as the ability to create and share your own custom transformations with Python, Javascript, or JSON. Without relying on dbt for transformations, easily apply and code your own transformations right in Nexla without constraint. Fivetran transformations are limited to only what is available through dbt once the data is in the warehouse, not along the way or between data products.
Difference #4: Unlimited Connectors
Fivetran offers a set of pre-coded connectors developed and launched by their team. Nexla offers an open-ended connector template for any type of data from APIs, webhooks, FTP, SFTP, spreadsheets, email, and warehouses that your data might be stored in - all both as sources and destinations. Fivetran can only write out to your databases, while Nexla serves all connectors as both source and destination. New connectors are simply configured, not coded, so they can be added in a matter of minutes. Nexla’s universal connector template ensures the right connector will always be available, or configurable, when needed.
Difference #5: Monitoring and Observability
Once flows are set up, ensuring quality and consistency requires powerful monitoring capabilities. Nexla has a full suite of monitoring tools that support data quality, including watching schema changes, cleaning, validation tools, and notifications for failed records to triage. Fivetran does not offer these features natively to customers.
Difference #6: Data Processing Controls
Nexla offers flexibility in how users can set up their data processing. Not only batch processing, but streaming, real-time, and API style processing are all available to configure as needed, which supports many use cases that are crucial to customers. A full suite of collaboration and sharing tools aims to accelerate the data operations process between and across teams. Fivetran flows are limited to batch processing only, which only applies to specific data use cases.
Difference #7: Built for Data Engineers
In addition to a no-code and low-code interface for data users, Nexla also offers complete platform capabilities for Data Engineers to automate the mundane tasks and tackle the most complicated challenges. Nexla’s powerful suite of APIs - the same ones available to our own UI developers - are accessible for custom solutions. The Nexla CLI offers complete control of Nexla from an engineer’s terminal of choice, allowing for automation through scripts to manage CI/CD for dev and production pipelines. JSON manifests of every flow enable managing versions in Github, while our Airflow operator further enables automation. Finally a complete Python SDK extends Nexla’s pre-built transformations to any custom code. Nexla is built for everyone, from non-coders to seasoned Data Engineers. Fivetran is primarily focused on data users rather than Data Engineers.