Best ETL Tools in 2026

ETL tools move data out of the systems that produce it and into the warehouse that reports on it.

This guide ranks them on the things that decide whether the pipeline still runs in a year: how they handle a source that changes its schema, what happens when a load fails halfway through, and how the bill behaves at volume.

Vendors can pay for visibility on this page. It never changes what an entry says about a product, including the criticism, and we earn nothing when you click through to a vendor. How that works.

In short

What ETL and data integration software does

ETL and data integration software extracts records from source systems, reshapes them into a common structure, and loads them into a warehouse, database or other application.

01

The top three

12 tools reviewed
02

How we ranked these

5 criteria, in order

Five things, in this order. Feature counts are not among them: they are the least useful comparison in software, because every vendor ticks every box.

  1. 01

    Setup effort in ETL and data integration software

    What the first ninety days of a ETL and data integration software rollout cost in hours, not in licence fees. A product that needs a partner engagement before it does anything is a different purchase from one a team configures in an afternoon.

  2. 02

    What ETL and data integration software really costs

    What the bill becomes once the modules a normal buyer of ETL and data integration software needs are added, and whether you can read that number without a sales conversation.

  3. 03

    Getting your data out of ETL and data integration software

    How your own data comes back out, in what format, and whether that export is included in the ETL and data integration software contract or billed as a project.

  4. 04

    Independence from the vendor

    Whether you can buy ETL and data integration software, run it and leave it on your own terms. This test decides most of the order on this page, and it is why the largest vendors in ETL and data integration software often sit below the smaller ones.

  5. 05

    Who the product is built for

    The size and shape of company each ETL and data integration software product was actually built for. Most regret in software comes from buying for a company you are not yet.

The fourth test decides most of the order on this page, and it is the reason the largest ETL and data integration software vendors sit below the smaller ones. A product with a published price, an export that works and no mandatory implementation partner is a product you can leave.

A platform suite that arrives with a quote, a partner and a two-year commitment may well be the better software and is still the harder decision to reverse. We rank ETL and data integration software for the buyer who has to live with that decision without a procurement department, which is a stated bias rather than a hidden one.

We do not publish a score out of ten. A number like 8.4 is a judgement dressed as a measurement, and nobody can check it.

What you can check is on this page: what each ETL and data integration tool costs, where the vendor is established, whether the price is published, and what we think it is bad at. Our full method is on the how we work page.

12tools reviewed
9publish a price
3have a free tier
5countries represented
03

Compared at a glance

12 tools
#ToolCountryPricingFree tier Right forNot for
#1AirbyteUnited StatesFree self-hosted open source; cloud priced by volume, publishedYesTeams with engineers who want to own and modify their pipelinesBusiness teams with nobody to run the platform
#2KeboolaCzechiaFree tier; consumption in platform minutes, publishedYesSmall European teams wanting extraction and orchestration in one placeOrganisations that want the warehouse to be the only platform
#3DataddoCzechiaPer data flow per month, published; free tierYesMarketing and finance teams needing predictable monthly integration costsReplicating large transactional databases into a warehouse
#4WeldDenmarkMonthly tiers by rows and models, publishedAnalytics teams building a first warehouse without hiring engineersVery high volume replication or complex modelling
#5Estuary FlowUnited StatesPer gigabyte moved plus per connector hour, publishedTeams needing warehouse data within seconds rather than hoursReporting needs that a nightly load already satisfies
#6MatillionUnited KingdomCredits consumed per hour, published rateWarehouse-centred teams wanting visual transformation analysts can readEngineering teams who prefer transformation as plain code
#7SemarchyFranceQuoted per organisation; licence with optional cloud hostingEuropean enterprises integrating on-premise systems with master data rulesSmall teams loading SaaS sources into a cloud warehouse
#8FivetranUnited StatesPer monthly active row, published calculatorTeams who want connectors that simply keep working, and will payBudget-sensitive teams with frequently updated tables
#9Qlik Talend CloudUnited StatesQuoted by capacity; enterprise agreementEnterprises needing data quality and profiling alongside their pipelinesTeams that adopted open source Talend and want continuity
#10Azure Data FactoryUnited StatesPer activity run and per integration unit hour, publishedAzure estates moving data between on-premise systems and the cloudTeams wanting managed SaaS connectors maintained for them
#11AWS GlueUnited StatesPer data processing unit hour, published; billed per secondAWS data teams comfortable writing and tuning Spark jobsLoading marketing and SaaS sources without engineering
#12Informatica IDMCUnited StatesConsumption units, quoted; annual commitmentLarge regulated estates with mainframes and strict lineage requirementsCloud-native teams with a warehouse and SaaS sources

Country is where the vendor is headquartered or contracts from, which is a different question from where your data is hosted. Where the two tell different stories, the entry says so.

04

The 12 tools, reviewed

Ranked

1. Airbyte · 2. Keboola · 3. Dataddo · 4. Weld · 5. Estuary Flow · 6. Matillion · 7. Semarchy · 8. Fivetran · 9. Qlik Talend Cloud · 10. Azure Data Factory · 11. AWS Glue · 12. Informatica IDMC

#1 Airbyte

Open source connectors you can host yourself and repair yourself

Ranked #1 of 12 in Best ETL Tools in 2026.

Free tierOpen sourceSelf-hostablePublished pricingNorth America

Airbyte is the honest answer to the exit question, because the connectors are source code you already have. When a niche source breaks, you are not waiting on a vendor's backlog.

The catalogue's size is a headline number that hides a distribution: the top fifty connectors are well maintained and the tail is not, so check the specific ones you need for recent commits and open issues. Self-hosted, it needs monitoring, upgrades and someone who understands the scheduler.

What stands out
  • Open source
  • Self-hosted
  • Largest connector catalogue
Where it costs you
  • Community connector quality varies widely
  • Self-hosting is real operational work
Right for

Teams with engineers who want to own and modify their pipelines

Wrong for

Business teams with nobody to run the platform

United StatesFree self-hosted open source; cloud priced by volume, published

#2 Keboola

Czech data platform billed by the minute of processing

Ranked #2 of 12 in Best ETL Tools in 2026.

Free tierPublished pricingEurope

Keboola solves the problem of the team that has a warehouse, a handful of sources and no data engineer. Orchestration, lineage and a catalogue come with the pipelines, hosted in the EU, and the free tier is usable for a genuine pilot.

The dependency it creates is broader than a pipeline tool's. If your transformations are written in Keboola and your schedules run there, then leaving means rebuilding the whole layer, not swapping a connector.

What stands out
  • EU hosting
  • Consumption billing
  • Orchestration included
Where it costs you
  • Transformations live inside the platform, which complicates leaving
  • Minute-based consumption is hard to estimate in advance
Right for

Small European teams wanting extraction and orchestration in one place

Wrong for

Organisations that want the warehouse to be the only platform

CzechiaFree tier; consumption in platform minutes, published

#3 Dataddo

Pipelines priced per flow, so the bill stops moving

Ranked #3 of 12 in Best ETL Tools in 2026.

Free tierPublished pricingEurope

The per-flow price is the argument. Every other vendor here bills something that grows when your business grows, which turns a data budget into a variable cost nobody controls. Dataddo charges for the pipe, not the water.

That works because it targets advertising and SaaS sources where volumes are modest. Point it at a busy production database and both the model and the product stop fitting, and the transformation layer will send you to the warehouse anyway.

What stands out
  • Published price
  • Predictable unit
  • EU vendor
Where it costs you
  • Basic transformation capabilities
  • Not designed for large database replication
Right for

Marketing and finance teams needing predictable monthly integration costs

Wrong for

Replicating large transactional databases into a warehouse

CzechiaPer data flow per month, published; free tier

#4 Weld

Danish ELT with SQL transformations and lineage included

Ranked #4 of 12 in Best ETL Tools in 2026.

Published pricingEurope

Weld's proposition is that one product gets a small company from scattered sources to reportable data, with the transformations, scheduling and lineage in the same place and prices you can read online.

For a company of a hundred people that is usually enough, and the European base helps with procurement. Above that scale, the model graph outgrows the tooling and you begin wanting dedicated transformation tooling, at which point you are paying Weld mostly for extraction.

What stands out
  • EU vendor
  • SQL transformations
  • Published price
Where it costs you
  • Shorter connector list than the larger vendors
  • Transformation layer strains on complex model graphs
Right for

Analytics teams building a first warehouse without hiring engineers

Wrong for

Very high volume replication or complex modelling

DenmarkMonthly tiers by rows and models, published

#5 Estuary Flow

Log-based change capture that also backfills the history

Ranked #5 of 12 in Best ETL Tools in 2026.

Published pricingNorth America

Estuary reads the database write-ahead log, so it captures every change without polling and without hammering the source with queries. Backfill and live tailing are the same pipeline, which removes the usual awkward switchover. Ask honestly whether you need it.

Most reporting is fine on a nightly schedule, and streaming means monitoring lag, handling replay and understanding what happens when the consumer falls behind. Buy it for operational use cases, not because real time sounds better.

What stands out
  • Change data capture
  • Streaming
  • Published price
Where it costs you
  • Fewer connectors than the established vendors
  • Streaming adds operational complexity over nightly batch
Right for

Teams needing warehouse data within seconds rather than hours

Wrong for

Reporting needs that a nightly load already satisfies

United StatesPer gigabyte moved plus per connector hour, published

#6 Matillion

Transformation pushed down into the warehouse you already pay for

Ranked #6 of 12 in Best ETL Tools in 2026.

Published pricingEurope

Pushdown is the right architecture: the warehouse is already sized and paid for, so running transformation anywhere else duplicates compute. Matillion adds a visual layer over it that analysts genuinely use, which widens who can maintain the pipeline.

The economics need watching. You pay Matillion credits for the duration of the run and the warehouse for the compute, so an unoptimised job is billed by two suppliers, and nobody notices until the quarterly invoice.

What stands out
  • Pushdown transformation
  • Warehouse native
  • Credit pricing
Where it costs you
  • Credits are consumed by job runtime, so slow jobs cost twice
  • Visual pipelines are awkward to review in version control
Right for

Warehouse-centred teams wanting visual transformation analysts can read

Wrong for

Engineering teams who prefer transformation as plain code

United KingdomCredits consumed per hour, published rate

#7 Semarchy

French integration engine with master data and quality attached

Ranked #7 of 12 in Best ETL Tools in 2026.

Self-hostablePricing on requestEurope

Semarchy comes from the classic integration world, where the hard part was never the connector but the reconciliation: which customer record is the real one, and what to do with the three variants.

Bundling that with the movement of data makes sense for manufacturers and public bodies with systems older than the cloud. It is the wrong shape for a startup with a warehouse and twelve SaaS sources, and the buying process assumes a project rather than a card payment.

What stands out
  • French vendor
  • On-premise option
  • Master data
Where it costs you
  • Quoted pricing with an implementation partner expected
  • Tooling feels older than the SaaS competition
Right for

European enterprises integrating on-premise systems with master data rules

Wrong for

Small teams loading SaaS sources into a cloud warehouse

FranceQuoted per organisation; licence with optional cloud hosting

#8 Fivetran

Managed connectors that keep working without anyone watching them

Ranked #8 of 12 in Best ETL Tools in 2026.

Published pricingNorth America

Fivetran sells the absence of a problem: connectors that survive source API changes, schema drift that lands as new columns rather than as a failed load, and no maintenance work for your team. That is worth real money and it is why it stays on shortlists.

The pricing unit is the risk. Monthly active rows count any row touched, so a table with constant updates costs the same as one with constant inserts, and forecasting means running a real load first.

What stands out
  • Managed connectors
  • Schema drift handling
  • Row pricing
Where it costs you
  • Monthly active row pricing is volatile and hard to predict
  • No transformation layer of its own
Right for

Teams who want connectors that simply keep working, and will pay

Wrong for

Budget-sensitive teams with frequently updated tables

United StatesPer monthly active row, published calculator

#9 Qlik Talend Cloud

The old Talend stack inside a larger analytics company

Ranked #9 of 12 in Best ETL Tools in 2026.

Open sourcePricing on requestNorth America

The data quality tooling is the reason to consider it: profiling, standardisation and rules that produce evidence an auditor accepts, sitting in the same product as the pipelines. For a regulated enterprise that is a real consolidation.

The history is the problem. Organisations that built on the open source Studio have had to plan migrations they did not choose, and the current product is priced and packaged for large accounts rather than for the teams that adopted Talend originally.

What stands out
  • Data quality
  • Wide connectivity
  • Enterprise contract
Where it costs you
  • Migration from legacy Talend Studio projects is difficult
  • Roadmap now follows Qlik's analytics priorities
Right for

Enterprises needing data quality and profiling alongside their pipelines

Wrong for

Teams that adopted open source Talend and want continuity

United StatesQuoted by capacity; enterprise agreement

#10 Azure Data Factory

The pipeline runner already inside your Azure agreement

Ranked #10 of 12 in Best ETL Tools in 2026.

Self-hostablePublished pricingNorth America

Data Factory wins on procurement and on reach: it is already in the agreement, and the self-hosted integration runtime pulls from databases behind the firewall without opening anything to the internet. That combination is hard to beat for a hybrid estate.

Day to day it is unpleasant. Pipelines are configured through a slow interface, failures are investigated in run histories, and because each activity run is billed, teams cram logic into fewer activities and make the pipelines harder to follow.

What stands out
  • Azure native
  • Per-run pricing
  • Hybrid runtime
Where it costs you
  • Authoring and debugging experience is poor
  • Per-activity pricing distorts pipeline design
Right for

Azure estates moving data between on-premise systems and the cloud

Wrong for

Teams wanting managed SaaS connectors maintained for them

United StatesPer activity run and per integration unit hour, published

#11 AWS Glue

Serverless Spark jobs for teams that already write code

Ranked #11 of 12 in Best ETL Tools in 2026.

Published pricingNorth America

Glue is infrastructure rather than a product, and priced accordingly: per second of processing capacity, with no licence sitting on top. For heavy transformation over files in object storage, nothing here is cheaper.

It assumes a team that already writes Spark, tunes partitioning and reads driver logs. It also does not solve the boring half of the job, which is extracting from a hundred SaaS APIs, so most estates end up pairing Glue with something from higher on this page.

What stands out
  • Serverless Spark
  • AWS native
  • Code-first
Where it costs you
  • No managed SaaS connectors worth relying on
  • Requires Spark skills to use properly
Right for

AWS data teams comfortable writing and tuning Spark jobs

Wrong for

Loading marketing and SaaS sources without engineering

United StatesPer data processing unit hour, published; billed per second

#12 Informatica IDMC

The enterprise incumbent, priced in units nobody forecasts

Ranked #12 of 12 in Best ETL Tools in 2026.

Self-hostablePricing on requestNorth America

Informatica remains the answer when the sources are old, the auditors are serious and the estate is too large for a tool a team maintains itself. Connectivity to mainframe and legacy applications is real and rare.

The costs are equally real: consumption units that bundle unrelated activities, an annual commitment negotiated in advance, and engineers who charge more because the skill is scarce. Before signing, price the same three pipelines on two other tools and put the difference in the paper.

What stands out
  • Enterprise governance
  • Mainframe connectivity
  • Consumption pricing
Where it costs you
  • Consumption unit pricing is difficult to forecast
  • Needs specialist skills that command a premium
Right for

Large regulated estates with mainframes and strict lineage requirements

Wrong for

Cloud-native teams with a warehouse and SaaS sources

United StatesConsumption units, quoted; annual commitment
06

How to choose ETL and data integration software

ETL and data integration software extracts records from source systems, reshapes them into a common structure, and loads them into a warehouse, database or other application. The differences that matter are rarely in the feature list, so this is the order we would work through them.

  1. 01

    Decide whether you need a published price

    9 of the 12 tools here publish what they cost; the other 3 quote per organisation, which means a sales conversation before you can compare anything. If you are buying without a procurement function, start with the ones that publish: Airbyte, Keboola, Dataddo, Weld, Estuary Flow, Matillion, Fivetran, Azure Data Factory, AWS Glue.

  2. 02

    Work out what the first ninety days cost in time

    Licence cost is the number in the contract; setup effort is the number that surprises people. Ask every shortlisted vendor who does the configuration, how long it took the last customer of your size, and what happens if that person leaves halfway.

  3. 03

    Check the exit before the entry

    Ask for an export of your own data in a format you can open, and ask whether it is included or billed as a project. A vendor that hesitates here is telling you what renewal negotiations will feel like in three years.

  4. 04

    Match the tool to the size you are, not the size you plan to be

    Most regret in this category comes from buying for a headcount that never arrived. The entry-level products here are not worse; they are aimed at a different company.

  5. 05

    Decide how much the jurisdiction matters

    These 12 vendors are established in 5 countries across 2 regions (North America 7, Europe 5). Where a vendor is established decides which government can compel access to what it holds, which is a different question from where the servers are. For most buyers that is a factor, not a veto.

  6. 06

    Consider whether you want the source

    2 of these are open source, which means you can host them yourself and read what they do with your data. That control is real, and so is the maintenance it hands you.

Transform before the warehouse, or inside it

The old pattern transformed data in a dedicated engine and loaded the result: Semarchy, Informatica IDMC and Qlik Talend Cloud are built this way, and it still suits estates where the destination is not one big warehouse. The current pattern loads raw data first and transforms it with the warehouse's own compute, which is what Fivetran and Airbyte assume and what Matillion turns into a visual product by pushing the work down into Snowflake or BigQuery.

ELT is usually cheaper, because you already pay for that compute, and easier to debug, because the raw data is still there to compare against. It also means your warehouse bill absorbs the transformation cost, so watch both invoices together.

  • Decide where transformation runs before comparing connector lists.
  • If you choose ELT, model the extra warehouse compute in the same business case.
  • Keep raw loaded data for long enough to reprocess a bad transformation.

Batch or streaming, and whether you actually need seconds

A nightly batch is simple, cheap and sufficient for most reporting. Change data capture, which Estuary Flow does as its core function and Fivetran and Airbyte offer for databases, reads the transaction log and delivers changes continuously. It puts far less load on the source than repeated polling, which matters for a production database that also serves customers.

The cost is operational: you now monitor lag, handle replays after an outage, and reason about what a consumer sees mid-transaction. Choose streaming for operational uses, fraud checks, stock levels, service dashboards. Choose batch for finance and management reporting, and do not let a vendor sell you seconds you will never look at.

  • Ask which business decision changes if data is an hour old instead of a minute.
  • Check what change capture does to your source database's log retention settings.
  • Test a replay after a deliberate outage before committing to streaming.

Schema drift and the load that fails halfway

Connector counts are marketing; the real question is what happens on a Tuesday when a source adds a column or renames one. Good tools land the new column in the warehouse and carry on. Weaker ones fail the whole load, or quietly drop the field, which is worse. Fivetran handles this better than anything else here and charges for it.

The second question is idempotency: if a load dies at seventy percent, does rerunning it duplicate rows or resume cleanly. Ask about the state the pipeline keeps between runs, and about how deleted source records are represented, because a soft delete that never reaches the warehouse produces reports that quietly overstate everything.

  • During the trial, add and rename a column in a source and watch what arrives.
  • Kill a running load and rerun it; count the rows afterwards.
  • Ask how deletions in the source are reflected in the destination.

Rows, connectors or compute: three bills that behave differently

Fivetran counts monthly active rows, so a table updated constantly costs the same as one growing constantly, and a chatty source can double your bill without adding information. Dataddo charges per flow, which is flat and predictable but assumes modest volumes.

Keboola bills processing minutes, AWS Glue and Azure Data Factory bill compute, and Matillion bills credits by runtime, so all four reward efficient jobs and punish careless ones. Informatica IDMC uses consumption units that mix several activities into one currency. Airbyte self-hosted charges nothing and bills you in staff time instead. Run a real month of your own data through the two finalists before signing anything annual.

  • Load one real month of data during the trial and read the resulting bill.
  • Ask what an update to an existing row costs compared with an insert.
  • Check the price of a full historical resync, which you will need at least once.

What goes wrong most often when buying ETL and data integration software

  • Choosing on connector count. You need eleven connectors and only their quality matters; the other four hundred are for someone else's stack.
  • Sizing the contract on today's volumes. Row-based pricing follows business growth, and the renewal arrives after the growth, not before it.
  • Assuming a failed load can simply be rerun. Ask about resumption and duplicates before you find out during a month-end close.
  • Putting transformation logic somewhere it cannot be reviewed. If pipelines are not in version control, nobody can say what changed when the numbers moved.
07

Frequently asked questions

11 answers
What is the best ETL and data integration in 2026?

Airbyte leads our ranking of 12. The only entry you can run on your own servers, read the connector source and fix when it breaks, which is the independence argument in one sentence.

The catalogue is the largest because anyone may contribute, and that is the weakness too: community connectors range from production-grade to abandoned. Self-hosting is genuine operational work, and the cloud pricing model has been revised more than once.

How did you rank these ETL and data integration tools?

On what separates products after the demo: how much setup the first ninety days take, what the price becomes once the modules a normal buyer needs are added, how your data comes back out, whether you can buy and leave it without a partner engagement, and who the product is genuinely for.

That fourth test is why the large platform suites usually sit lower here than their market share would suggest. Not on feature counts, and not on a score we invented.

Which ETL and data integration tools publish their pricing?

9 of the 12, with the pricing model each one publishes:

  • Airbyte: Free self-hosted open source; cloud priced by volume, published.
  • Keboola: Free tier; consumption in platform minutes, published.
  • Dataddo: Per data flow per month, published; free tier.
  • Weld: Monthly tiers by rows and models, published.
  • Estuary Flow: Per gigabyte moved plus per connector hour, published.
  • Matillion: Credits consumed per hour, published rate.
  • Fivetran: Per monthly active row, published calculator.
  • Azure Data Factory: Per activity run and per integration unit hour, published.
  • AWS Glue: Per data processing unit hour, published; billed per second.

The other 3 quote per organisation.

Is there a free ETL and data integration tool?

Airbyte, Keboola, Dataddo offer a free tier or a free self-hosted edition. Read what the free tier excludes before you plan around it.

Which ETL and data integration tools are open source?

Airbyte, Qlik Talend Cloud. Open source means you can read what the product does with your data and run it yourself. It does not mean the hosted edition is free.

Which ETL and data integration tools can you host yourself?

Airbyte, Semarchy, Azure Data Factory, Informatica IDMC. The other 8 are sold as a hosted service only, which means the question of where your data sits is answered by the vendor, not by you.

Where are these ETL and data integration vendors established?

In 5 countries across 2 regions: North America 7, Europe 5.

  • Airbyte is established in the United States.
  • Keboola is established in Czechia.
  • Dataddo is established in Czechia.
  • Weld is established in Denmark.
  • Estuary Flow is established in the United States.
  • Matillion is established in the United Kingdom.
  • Semarchy is established in France.
  • Fivetran is established in the United States.
  • Qlik Talend Cloud is established in the United States.
  • Azure Data Factory is established in the United States.
  • AWS Glue is established in the United States.
  • Informatica IDMC is established in the United States.

Establishment decides whose courts and whose disclosure laws apply, which is a separate question from where the data is hosted.

What should you use instead of Airbyte?

Keboola and Dataddo are the next two on this page. Keboola is for small European teams wanting extraction and orchestration in one place; Dataddo is for Marketing and finance teams needing predictable monthly integration costs.

All 12 are ranked here with what each one is bad at.

Who should not buy Airbyte?

Business teams with nobody to run the platform. Community connector quality varies widely.

Do you get paid for these rankings?

Vendors can pay for visibility, which affects where and how prominently a product appears. It does not change a word of what the entry says about that product, including the criticism, and it cannot buy inclusion for something that does not belong in the category.

We take no commission when you click through to a vendor and we do not know whether you bought anything. The full arrangement is on our disclosure page.

How often is this ETL and data integration guide updated?

Whenever the facts move: a price change, an acquisition, a product that stops being maintained. The published and updated dates at the top of the page are real, and a review means someone went back to the vendor documentation rather than bumping a date.

Tools reviewed

12 products

For software vendors

Not on this list?

These 12 products are the ones we judged worth ranking in ETL and data integration. If yours belongs here and is missing, tell us what it does and who it is for, and we will look at it. Inclusion is an editorial call and it is not for sale — but nobody gets considered for a list they were never put in front of.

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