Compare the top ETL tools in 2026. Fivetran, Airbyte, Matillion, Informatica, Qlik Talend Cloud, Hevo, AWS Glue and more, with pricing models and best-fit use cases.
Every analytics dashboard, every AI agent and every board report sits on top of a pipeline someone had to build. ETL tools are the layer that extracts data from SaaS apps, databases and event streams, transforms it into something usable, and loads it into a warehouse or lakehouse where the rest of the business can reach it.
The category has changed a lot in the last two years. Most vendors now default to ELT, loading raw data first and transforming inside the warehouse. Change data capture has gone from an enterprise add-on to a checkbox. Pricing has fragmented into rows, events, credits, capacity bands and flat fees, which makes like-for-like comparison harder than it should be. And nearly every vendor has bolted on an AI assistant that promises to write your pipelines for you.
This list covers ten ETL and ELT platforms worth shortlisting in 2026, from managed SaaS connectors to open-source engines and the native tools inside AWS and Azure. For each one we cover what it does well, how it charges, and who it suits. If you are also choosing a destination, our guide to the top Snowflake consulting partners and our piece on the best way to migrate from a data warehouse to a lakehouse pair well with this one.
ETL Tools At A Glance
Tool
Approach
Pricing model
Best for
Fivetran
Managed ELT, 700+ connectors
Monthly Active Rows, free tier to 500K MAR
Teams that want zero-maintenance pipelines
Airbyte
Open-source ELT, 600+ connectors
Free self-hosted; Cloud from $10/month on credits
Engineering teams that want control and long-tail sources
Matillion
Cloud-native ETL/ELT with Maia AI agents
Credits across Developer, Teams and Scale editions
Warehouse-centric teams on Snowflake, Databricks, BigQuery or Redshift
Informatica IDMC
Enterprise data management platform
Consumption-based IPUs
Large enterprises with governance and MDM needs
Qlik Talend Cloud
Integration plus data quality and trust scoring
Capacity bands by data moved and job hours
Organisations that need quality and lineage built in
Hevo Data
No-code ELT, 150+ connectors
Events per month, free tier to 1M events
Lean data teams that want to be live in an afternoon
Integrate.io
Low-code ETL, ELT/CDC and API generation
Fixed monthly fee
Ops teams that want predictable spend
Stitch
Simple managed ELT
Rows per month, from $100/month
Small teams with straightforward batch loads
AWS Glue
Serverless Spark ETL and Data Catalog
$0.44 per DPU-hour, Flex at $0.29
AWS-native shops with Spark skills
Azure Data Factory
Cloud integration service with SSIS lift-and-shift
Per activity run and DIU-hour
Microsoft shops and SSIS migrations
Best ETL Tools Options In 2026
1. Fivetran — The Managed Connector Standard Everyone Else Is Measured Against
Fivetran built the fully managed ELT category and still defines it. You pick a source, authorise it, choose a destination, and the schema, normalisation, incremental syncs and API changes are handled for you. The catalogue now runs to more than 700 managed connectors, plus a newer Activations product that pushes modelled data back into 200+ business tools, so the platform covers reverse ETL as well as ingestion.
Pricing is by Monthly Active Rows, the number of distinct rows inserted, updated or deleted in a month, and the per-row rate falls as volume grows. There is a Free plan good for 500K MAR, a Standard plan with 15-minute syncs and unlimited users, an Enterprise tier with one-minute syncs and VPN tunnels, and a Business Critical tier with customer-managed keys and PCI DSS Level 1. Annual contracts discount up to 22 percent.
The trade-off is cost at scale. MAR bills can climb quickly on high-churn tables, and there is a base charge per connection outside the free tier. If your team would rather spend money than engineering hours and wants pipelines nobody has to babysit, Fivetran remains the safe default.
2. Airbyte — Open-Source ELT With the Longest Connector Tail
Airbyte is the open-source answer to Fivetran. The Core engine is free to self-host with no volume cap, and the community has pushed the catalogue past 600 connectors, with a Connector Builder that lets you stand up a new API source in YAML or Python in under an hour. That long tail is the reason many teams pick it: if a niche SaaS tool has an API, someone has probably already written the Airbyte connector.
Airbyte Cloud removes the hosting burden. The Standard plan starts at $10 a month with a handful of included credits and volume billing at $2.50 per credit after that. The Plus and Pro tiers move to capacity-based Data Workers on an annual commitment and add SSO, RBAC, faster sync frequencies and custom mappings, while Enterprise Flex covers hybrid and multi-cloud deployments. Vector store destinations and CDC are in the box, which makes it a common choice for feeding retrieval pipelines.
The honest cost of self-hosting is infrastructure plus engineering time, and failed syncs on Cloud still consume credits. Airbyte suits teams with the engineering depth to run it and a source list too unusual for the managed vendors.
3. Matillion — Warehouse-Native Transformation With an Agentic Layer
Matillion’s Data Productivity Cloud is a low-code canvas for building both ingestion and transformation pipelines that run pushdown inside Snowflake, Databricks, BigQuery or Redshift. It sits between the pure connector vendors and the heavyweight enterprise suites: more transformation power than Fivetran or Stitch, far less setup than Informatica.
The 2026 story is Maia, Matillion’s agentic data workforce, which builds, documents and orchestrates pipelines from natural-language prompts and is available across every edition. Pricing is credit-based, with credits consumed by task hours and extra developer seats. The Developer edition covers one developer and light workloads, Teams adds audit logs and SLAs for five developers, and Scale brings SSO, hybrid deployment, lineage, CDC and extended log retention. You can buy through AWS, Azure or Snowflake marketplaces, which helps teams burn down committed cloud spend.
Matillion is the pick for teams that have already committed to a cloud warehouse and want their SQL and Python transformations, orchestration and ingestion in one governed tool.
4. Informatica — Enterprise Data Management, Now Part of Salesforce
Informatica’s Intelligent Data Management Cloud is the broadest platform on this list. Cloud Data Integration is the ETL and ELT engine, but it ships alongside data catalog, data quality, governance, privacy and master data management, all driven by the CLAIRE AI layer that recommends mappings, detects anomalies and automates classification.
The big change is ownership. Salesforce completed its acquisition of Informatica in November 2025, positioning IDMC as the governed data foundation for Agentforce and tying it into MuleSoft and Tableau. For Salesforce-heavy enterprises that is a strong signal; for everyone else it is worth watching how roadmap priorities shift. Pricing runs on consumption-based Informatica Processing Units, which are flexible but require careful forecasting.
This is not a tool for a five-person data team. It is the choice when regulatory pressure, MDM and lineage matter as much as moving rows, and when a single vendor across integration and governance simplifies procurement.
5. Qlik Talend Cloud — Integration With Data Quality and Trust Scores Built In
Qlik Talend Cloud is the product of Qlik’s 2023 acquisition of Talend, and it combines Qlik’s replication and CDC engine with Talend’s transformation and data quality tooling. The differentiator is trust: every dataset carries a Trust Score built from quality, validity and lineage metrics, so analysts can see whether a table is fit for use before they build on it.
The platform is sold in four use-case-centric editions on a capacity model. Capacity is measured two ways, by data moved in gigabytes per month, with initial full loads free, and by job executions and run hours, with flexible bands you can add as usage grows. Usage dashboards let central teams allocate cost back to business units.
Qlik Talend Cloud makes sense for mid-size and large organisations that want quality and lineage as first-class features rather than a separate observability purchase, and especially for existing Qlik Sense customers.
6. Hevo Data — No-Code Pipelines Live in an Afternoon
Hevo is built for lean data teams that need reliable pipelines without a data engineer on staff. Setup is entirely no-code, the 150+ connectors cover the common SaaS, database and event sources, and pipelines run on schedules down to a few minutes with streaming available on higher tiers. Transformations can be done pre-load with Python or drag-and-drop, or post-load with Hevo Models.
Pricing is by events, meaning records processed per month. The Free tier covers 1M events with five users and a limited connector set, Starter covers 5M events for around $239 a month on annual billing with 150+ connectors, Professional scales from 20M to 100M events with unlimited users and streaming, and Business Critical adds HIPAA, RBAC, SSO and a one-hour support SLA. As with any consumption model, budget predictability drops as volume climbs.
Hevo suits startups and mid-market teams that want a Fivetran-like experience at a lower entry price and can live with a smaller connector catalogue.
7. Integrate.io — Fixed-Fee ETL, ELT, CDC and API Generation in One Platform
Integrate.io stands out for how it charges rather than what it connects. Instead of rows, events or credits, it sells a flat monthly subscription, with its Core plan listed at $1,999 a month, and positions that predictability as the main reason to switch from usage-based rivals. The San Francisco company has been around since 2012 and serves operations and analytics teams rather than deep engineering groups.
The platform bundles four products: a low-code ETL designer with rich transformation components, an ELT and CDC service for near-real-time replication, an API generation layer that exposes datasets as REST endpoints, and data observability for monitoring pipeline health. Support is hands-on, with solution engineers included in onboarding.
If your finance team is tired of variable data bills and your volumes are high enough that usage pricing has become painful, Integrate.io is the platform to model against.
8. Stitch — Simple, Cheap Managed ELT for Small Teams
Stitch is the lightweight option. Acquired by Talend in 2018 and now part of Qlik, it does one thing: extract data from sources and load it into a warehouse on a schedule, with minimal transformation and no real-time replication. That simplicity is the appeal for teams that just need Salesforce, HubSpot, Postgres and a few ad platforms landing in Snowflake or BigQuery every hour.
Pricing is row-based and starts at $100 a month on the Standard plan, which covers up to 300M rows, ten sources, one destination and five users. Advanced and Premium plans are annual, add more destinations and unlock the Enterprise connector set. Overages apply beyond your row tier, and you will need dbt or a similar tool for transformation.
Stitch is right for small companies and single-analyst teams who want the lowest entry cost and do not need CDC, streaming or heavy transformation. Larger teams will likely outgrow it.
9. AWS Glue — Serverless Spark ETL Inside the AWS Account You Already Have
AWS Glue is the native ETL service for AWS. It runs serverless Apache Spark, Python Shell and Ray jobs, catalogues your S3, RDS and Redshift data in the Glue Data Catalog, and includes Glue Studio for visual job authoring, DataBrew for no-code data preparation and Glue Data Quality for rule-based checks. Because it sits inside your AWS account, IAM, VPC and billing are already solved.
Pricing is by Data Processing Unit hours, at $0.44 per DPU-hour for standard jobs or $0.29 with Flex execution for batch workloads that can tolerate delays. Jobs bill with a one-minute minimum and a two-DPU floor, crawlers carry a ten-minute minimum, and the Data Catalog is free for the first million objects and requests per month. Job bookmarks, Parquet conversion and right-sized DPU allocation are the usual levers for cutting the bill.
Glue is the right call for AWS-native organisations with Spark or Python skills in-house. It is not a SaaS connector catalogue, so teams pulling from dozens of business applications often pair it with Fivetran or Airbyte for ingestion.
10. Azure Data Factory — Microsoft’s Integration Service and the SSIS Escape Route
Azure Data Factory is Microsoft’s cloud data integration service, offering visual pipelines, mapping data flows for code-free Spark transformations and a large connector library that is naturally strongest across SQL Server, Dynamics, SharePoint, Synapse and the rest of the Microsoft estate. Its most practical feature for many enterprises is the ability to lift and shift existing SSIS packages and run them unchanged in the cloud.
Pricing has more moving parts than Glue: you pay per activity run, per Data Integration Unit hour for copy activity, per vCore-hour for data flows, and for pipeline orchestration time. It is cheap for light workloads and worth modelling carefully for heavy ones. Data Factory capabilities are also being carried forward into Microsoft Fabric, so teams on that platform get the same pipeline engine.
Choose Data Factory if you are a Microsoft shop, are migrating SSIS workloads, or are standardising on Fabric and Power BI for analytics.
How To Choose An ETL Tool
Do you need ETL, ELT or both?
Most modern warehouses are cheap enough to load raw data and transform in SQL afterwards, which is why Fivetran, Airbyte, Hevo and Stitch are ELT first. If you must transform before load for compliance, masking or cost reasons, or you have complex multi-source joins, Matillion, Informatica, Qlik Talend Cloud, Integrate.io, Glue and Data Factory give you a proper transformation layer.
Which pricing model matches your data profile?
Row and event models are cheap at low volume and expensive on high-churn tables. Credit and capacity models reward predictable, scheduled workloads. Flat fees remove surprises but cost more at the low end. Run your real table sizes and update frequencies through each vendor’s calculator before you sign; the cheapest plan on paper is rarely the cheapest at month twelve.
How unusual are your sources?
If everything you need is in the top 100 SaaS tools, any managed vendor will do. If you rely on niche APIs, legacy databases or internal systems, check the catalogue line by line and favour platforms with a connector builder or open-source community, which is where Airbyte earns its place.
Do you need real-time or is hourly fine?
Change data capture and streaming add cost and complexity. Stitch is batch only, Hevo reserves streaming for higher tiers, and Fivetran’s one-minute syncs live on Enterprise. Be honest about which dashboards actually need sub-hour freshness.
How much governance do you need in the tool itself?
Lineage, quality rules, catalogues and trust scores are built into Informatica and Qlik Talend Cloud and available in Matillion’s Scale edition. The connector-first vendors expect you to buy those separately. In regulated industries that difference often decides the shortlist.
Who will maintain it?
Self-hosted Airbyte, Glue and Data Factory assume engineers on call. Fivetran, Hevo, Stitch and Integrate.io assume you would rather not. Match the tool to the team you have, not the team you plan to hire.
Conclusion
There is no single best ETL tool in 2026, only the best fit for your sources, your warehouse, your team and your tolerance for variable bills. Fivetran and Hevo are the fastest way to reliable managed pipelines, Airbyte is the open-source route with the widest reach, Matillion is the strongest warehouse-native transformation layer, and Informatica and Qlik Talend Cloud bring governance for enterprises that cannot separate integration from compliance. Integrate.io and Stitch bracket the market on pricing philosophy, while Glue and Data Factory are the obvious choices when you are already living inside AWS or Azure.
Shortlist two or three, run a proof of concept on your ugliest source, and price it on twelve months of realistic growth. That exercise will tell you more than any comparison table, including this one. For the downstream side of the stack, see our roundup of the top web analytics tools in 2026.
