If you’re shopping for Informatica alternatives, you’re probably dealing with one of three things.
The cost. Informatica licensing is expensive and opaque. Most organizations end up paying for far more than they use.
The Salesforce acquisition. Salesforce bought Informatica in November 2025. If you’re worried about price increases or roadmap changes, now is a good time to evaluate before renewal.
Your team has changed. Analysts, finance leads, and ops managers need to work with data directly. Informatica was built for IT departments, not for them.
Informatica alternatives at a glance
Tool | Best for | Technical level | Starting price |
|---|---|---|---|
Mammoth Analytics | Business user self-service | Low (No-code) | From $16/mo |
Azure Data Factory | Microsoft/Azure teams | High | Pay-as-you-go |
Fivetran | Automated data ingestion | Medium | Usage-based |
Talend (Qlik) | Enterprise ETL + governance | High | Enterprise quote |
AWS Glue | Data engineering teams on AWS | High | Pay-as-you-go |
Matillion | Cloud data warehouse transformation | Medium-High | Usage-based |
Dell Boomi | Application-to-application integration | Medium | Enterprise quote |
Stitch | Simple, low-cost ingestion | Low | From $100/mo |
1. Mammoth Analytics: Best for business user self-service
Most Informatica alternatives on this list are still built for data engineers. Mammoth is the exception.
Mammoth is a no-code data preparation and transformation platform for analysts, finance teams, and operations managers. Users describe what they need in plain language and the platform builds the pipeline. No code, no IT ticket.
It connects to hundreds of sources including Salesforce, SAP, BigQuery, Snowflake, HubSpot, and MySQL. It also includes AI-powered dashboard creation, so you can go from raw data to a published dashboard in under 15 minutes.
Pricing
Business tier starts at $16/month billed annually for teams of 5+ users. Enterprise pricing is custom, typically starting around $75,000 annually. See the Mammoth pricing page for current tiers.
Proof it works
Starbucks processes over one billion rows monthly across 17 countries using Mammoth. Monthly reporting that used to take 20 days now takes hours.
Arla Foods saved 1,200 manual hours annually. RethinkFirst cut a 30-hour monthly process down to 4 hours.
Good fit if:
- Your analysts or finance team need data access without IT involvement
- You’re paying for Alteryx or Informatica but only using a fraction of it
- You want a working pipeline in days, not months
Not the right fit if:
- You need full master data management or a data catalog
- Your team wants code-first workflows
- You have complex mainframe or CDC integration requirements
See how Mammoth compares to Alteryx
2. Azure Data Factory: Best for Microsoft/Azure teams
Azure Data Factory is Microsoft’s cloud ETL service. If your team is already on Azure, SQL Server, Synapse, or Power BI, it fits naturally into your existing stack.
ADF has a visual pipeline builder, but it’s a tool for data engineers. You need solid knowledge of Azure resources and data flow concepts to build and maintain real pipelines.
Pros vs. Informatica:
- Pay-as-you-go pricing avoids big upfront licensing costs
- Native integration across the Azure ecosystem
- Good hybrid environment support
- Broad connector library
Cons:
- Requires data engineering expertise
- Costs can grow quickly with data volume
- Poor fit for teams not already on Azure
Bottom line: Good for data engineering teams on Azure. Doesn’t solve the self-service problem.
3. Fivetran: Best for automated data ingestion
Fivetran moves data from your source systems into your data warehouse automatically. Its managed connectors handle schema changes, incremental updates, and pipeline monitoring without manual maintenance.
Fivetran is not a transformation platform. It’s typically paired with dbt for transformations.
Pros vs. Informatica:
- Fast setup, most connectors are live in hours
- No infrastructure to maintain
- Reliable with built-in monitoring and alerting
- Strong integrations with Snowflake, BigQuery, Redshift, and dbt
Cons:
- No transformation included, needs a separate tool
- Usage-based pricing gets expensive at scale
- Still requires technical resources to run
Bottom line: Great for data engineering teams building a modern ELT stack. Not a full Informatica replacement on its own.
4. Talend: Best for enterprise ETL with governance
Talend is the most direct Informatica competitor on this list. Now part of Qlik, it covers data integration, data quality, lineage, and compliance, with a feature set that closely mirrors Informatica.
If you’re leaving Informatica because of the Salesforce acquisition but still need enterprise-grade governance, Talend is worth a close look.
Pros vs. Informatica:
- Talend Open Studio (free) gives smaller teams a low-cost entry point
- Strong governance, lineage, and compliance tooling
- Qlik integration extends analytics capabilities
Cons:
- Cloud-native features lag behind newer tools
- Steep learning curve similar to Informatica
- Enterprise pricing is comparable to Informatica
- Not built for business user self-service
Bottom line: The closest like-for-like Informatica replacement for teams that need governance and are comfortable with technical complexity.
5. AWS Glue: Best for data engineering teams on AWS
AWS Glue is Amazon’s serverless ETL service with deep integration into the AWS ecosystem, including S3, Redshift, Athena, and Lambda.
Glue runs Apache Spark under the hood and auto-generates PySpark code. Most real-world use requires editing that code directly.
Pros vs. Informatica:
- Serverless, no infrastructure to manage
- Pay-per-use pricing
- Excellent integration with the AWS data stack
- Built-in Glue Data Catalog
Cons:
- Requires strong Python and Spark knowledge
- Debugging pipelines is more complex than in purpose-built ETL tools
- Limited to AWS, poor fit for multi-cloud environments
Bottom line: Cost-effective for data engineering teams on AWS. Not a tool for business users.
6. Matillion: Best for cloud data warehouse transformation
Matillion is a cloud-native ELT platform built for Snowflake, BigQuery, Redshift, and Databricks. Its main advantage is pushdown processing, which runs transformations directly in the warehouse rather than through a separate compute layer.
Pros vs. Informatica:
- Pushdown ELT maximizes performance on cloud warehouses
- More accessible interface than Informatica
- AI-assisted pipeline generation speeds up development
Cons:
- Requires a cloud data warehouse as the foundation
- Still needs data engineering expertise for complex logic
- Not designed for business user self-service
Bottom line: The strongest ELT-focused Informatica alternative for cloud data warehouse teams. Business user accessibility is limited.
7. Dell Boomi: Best for application integration
Dell Boomi is primarily an iPaaS tool. Its strength is connecting applications to each other, like Salesforce to SAP or ERP to CRM, rather than preparing data for analytics.
If your reason for leaving Informatica is application-to-application integration, Boomi is worth evaluating. If it’s analytics or business user access, it’s the wrong tool.
Pros vs. Informatica:
- Strong application integration capabilities
- More accessible low-code interface than traditional ETL
- Good pre-built connectors for SaaS apps
Cons:
- Built for app integration, not analytical data prep
- Not designed for high-volume analytical workloads
Bottom line: Right tool if connecting enterprise applications is the main need. Wrong tool if the goal is analytics or self-service data access.
8. Stitch: Best for simple, low-cost ingestion
Stitch (part of Talend) is a managed pipeline service for straightforward ingestion. It connects sources to data warehouses through pre-built connectors at a fraction of the cost of enterprise ETL tools.
Stitch doesn’t do transformation beyond basic normalization. It moves data.
Pros vs. Informatica:
- Starting around $100/month, the lowest entry price on this list
- Fast setup, most connections live in under an hour
- No data engineering expertise required for basic use
Cons:
- No transformation capabilities, needs separate tooling
- Limited connector library vs. enterprise tools
- Not built for enterprise scale
Bottom line: A good starting point for smaller teams that need basic, reliable ingestion. Not an enterprise Informatica replacement.
How to choose
Who needs to use the data?
If the answer is data engineers, any of these tools can work. If the answer is analysts, finance leads, or operations managers, only Mammoth was built for that.
What’s driving the change?
- Reducing cost: Mammoth, Stitch, AWS Glue, or ADF all cost less than Informatica at most scales
- Reducing IT dependency: Mammoth is the only tool purpose-built for this
- Modernizing your data stack: Fivetran plus dbt, or Matillion
- Application integration: Dell Boomi
- Enterprise governance without switching paradigms: Talend
What does your infrastructure look like?
- Fully on Azure: Azure Data Factory
- Fully on AWS: AWS Glue
- Cloud data warehouse (Snowflake, BigQuery, Redshift): Matillion or Fivetran
- Multi-cloud or hybrid with business user teams: Mammoth Analytics
- Complex enterprise application landscape: Dell Boomi
Frequently asked questions
What happened to Informatica?
Salesforce completed its acquisition of Informatica in November 2025. Many organizations are evaluating alternatives ahead of renewal given uncertainty around pricing and roadmap direction.
Can Mammoth handle enterprise data volumes?
Yes. Starbucks processes over one billion rows monthly using Mammoth across 17 countries. The platform is cloud-native, auto-scales, and is SOC2 Type II, ISO 27001, and HIPAA-ready.
What connectors does Mammoth support?
Mammoth connects to hundreds of sources including SAP, Salesforce, Oracle, SQL Server, BigQuery, Snowflake, Databricks, Redshift, and HubSpot. Custom connectors can typically be built and deployed within a week. See the full connector list.
How long does it take to migrate from Informatica to Mammoth?
Most teams are up and running within days to a few weeks. Enterprise deployments typically take two to six weeks with structured implementation support.
Does Mammoth replace Tableau or Power BI?
For teams without existing BI tools, Mammoth handles the full journey from raw data to published dashboard. For teams already on Tableau or Power BI, Mammoth sits as the data preparation layer that feeds clean data into your existing tools. Read more on the Mammoth vs Tableau page.
The bottom line
Data engineering teams on Azure should look at ADF. Teams building a modern ELT stack should look at Fivetran plus dbt. Teams that need enterprise governance close to what Informatica offers should look at Talend.
But if the real problem is that your business teams are stuck waiting for IT, those tools don’t fix that. They just move the work to a different technical platform.
Mammoth is built for that specific problem. Business users can connect a data source, build a transformation pipeline, and publish a dashboard without IT involvement.