Informatica alternatives

4 tools to consider instead of Informatica, shown against it.

Informatica Talend Matillion Azure Data Factory AWS Glue
Vendor Informatica Inc. Qlik Matillion Microsoft Amazon Web Services
Pricing model Quote only Quote only Quote only Usage-based Usage-based
Free tier No No No Yes Yes
Deployment Cloud, Self-hosted Cloud, Self-hosted Cloud Cloud Cloud
Open source No No No No No
Best for Large enterprises needing integration bundled with governance, MDM and data quality at scale. Larger enterprises needing integration bundled with data quality and governance, not just pipeline movement. Analytics engineering teams wanting a visual, low-code ELT builder with warehouse-native transformation. Organizations standardized on Azure needing pipeline orchestration across cloud and on-premises sources. AWS-native teams needing serverless, pay-per-use ETL and a shared metadata catalog across analytics services.
Pricing

Consumption-based pricing metered in Informatica Processing Units (IPUs) shared across services; no public price list, quote required.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

Capacity-based subscription across four editions (Starter, Standard, Premium, Enterprise), metered by data volume, job executions and duration; no public price list.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

Consumption-based credit system tied to pipeline task hours and developer seats; only the entry Developer tier's trial is self-serve, the rest require a sales quote.

Developer Free trial
Teams Contact sales
Scale Contact sales

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Consumption pricing billed separately for pipeline orchestration (per 1,000 runs), data movement (per Data Integration Unit-hour), Data Flow execution (per vCore-hour) and external activity execution; first five low-frequency activities per month are free.

Orchestration & execution Billed per 1,000 activity/trigger/debug runs
Data movement Billed per Data Integration Unit-hour (DIU-hour)
Data Flow execution Billed per vCore-hour

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Billed per Data Processing Unit-hour (DPU-hour) for ETL jobs and crawlers, by the second; Data Catalog storage and requests are free up to the first million objects/accesses monthly.

ETL jobs & crawlers $0.44 per DPU-hour
Data Catalog Free for first 1M objects and 1M requests/month
DataBrew $1.00 per 30-min interactive session; $0.48 per node-hour for jobs

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features
  • Cloud and on-premises data integration
  • AI-assisted mapping (CLAIRE engine)
  • Master data management
  • Data quality and cataloging
  • API and application integration
  • Mass ingestion for bulk/CDC loads
  • Shared IPU consumption model across services
  • ETL/ELT pipeline design
  • Change data capture at scale (Standard+)
  • Data quality and profiling tools
  • Master data management
  • Data governance and cataloging (Enterprise)
  • Broad target/format support for transformation
  • AI-assisted data quality features
  • Low-code drag-and-drop pipeline canvas
  • Push-down transformation execution in the warehouse
  • Built-in Git version control
  • SQL and Python scripting components
  • Native dbt Core integration
  • Streaming change data capture (Scale tier)
  • Cross-cloud support for Snowflake, Databricks, BigQuery, Redshift
  • Visual pipeline designer and code-first authoring
  • Spark-backed Mapping Data Flows
  • Self-Hosted Integration Runtime for on-premises data
  • 90+ built-in connectors
  • Native orchestration of Databricks and HDInsight activities
  • Git-based CI/CD integration
  • Trigger-based and event-based scheduling
  • Serverless Apache Spark and Python ETL jobs
  • Auto-populated Hive-compatible Data Catalog
  • Crawlers for automatic schema discovery
  • Visual job authoring via Glue Studio
  • Zero-ETL integrations with other AWS services
  • Glue DataBrew for no-code data preparation
  • Schema Registry for streaming data

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