Exploring Top Alternatives to CData for ELT Solutions

Here is something that remains true in the era of AI. Data is still siloed and hard to access.

Are there plenty of tools that can help make data ingestion and ETL easier?

Yes, but they aren’t all created equal.

One established solution is CData.

According to CData, its products provide live connectivity and data replication across hundreds of enterprise data sources. CData is a data integration solution that provides pre-built connectors for integrating data from a wide variety of sources, including SQL and NoSQL databases, ERP (enterprise resource planning) software, CRM (customer relationship management) software, accounting platforms, marketing and e-commerce data, and more.

While CData can be the right solution for some, it’s far from the only option and may not be what you’re looking for.

For reasons such as cost, flexibility, scalability, or feature set, some businesses will be motivated to look for CData alternatives. Below, we’ll discuss how to evaluate various data connectivity solutions and review some of the leading contenders to CData.

What Is CData?

Two of CData’s relevant products for this comparison are CData Sync and CData Connect AI, formerly known as CData Connect Cloud. The product was renamed to Connect AI in 2025.

CData Sync moves and replicates data into databases, warehouses, and lakes using ETL, ELT, and CDC capabilities. It supports cloud, on-premises, and hybrid deployment. Its currently listed Standard configuration starts at $7,999 per year, with five standard connections and up to 100 million processed rows per month.

CData Connect AI primarily provides governed, live access to source systems. According to CData, it queries source systems directly rather than persistently replicating their data.

CData is used by organizations of all sizes and industries to connect, integrate, and synchronize data, either through live access or by moving data into a centralized location. The data can then be used for purposes such as real-time BI and analytics. However, CData might not be a good fit for every user. For example, while CData supports hundreds of data sources, this won’t cover every potential use case. If businesses need to extract data from a source that isn’t included in CData’s connector library, they might want to look elsewhere.

How to Evaluate Data Connectivity Software

If you’re not sure where to start looking for CData alternatives, take note of the criteria below to understand what you really need out of data connectivity software:

Integration capabilities: As discussed above, businesses should choose a data integration solution that offers pre-built connectors for their existing data sources and systems or makes it easy to build these connectors. This is a common decision point. As if a vendor don’t provide a connector out of the box, why use it? I will add, always ask if a company can add a new connector. Sometimes it’ll only take a week or so.

Performance and scalability: Data connectivity software should be able to handle growing data volumes and concurrent processes, especially if the business is planning future expansion.

Cost and licensing: Before you buy any software you need to understand how the product is priced. And they all seem to have their own approach to pricing. Some ELT and data integration solutions do it based on connectors, others rows of data processed, and of course also things like, data volume, compute and or some combination of all those.. They should also consider whether they need a managed cloud service, self-hosted software, or an on-premises deployment.

Support and community: Your choice of data integration software should have a healthy user community, as well as customer support and product documentation to help get answers to any questions and concerns.

Security and compliance: Data integration workflows often touch sensitive and confidential information, so a solution that adheres to industry best practices, standards, and regulations is critical.

3 Top CData Alternatives

Given the criteria listed above, below are some of the top data integration tools that are viable alternatives to CData.

CData Alternative #1: Estuary

Estuary offers hundreds of out of the box connectors. They make it easy for your data team to extract data from databases, SaaS applications, cloud storage platforms, warehouses, and lakehouses. One of its main differentiators is its support for both real-time and batch workloads. It calls this right time data.

This allows companies to use CDC to continuously replicate changes from a PostgreSQL database into Snowflake, for example, while using also using more traditional batch jobs for workloads that do not require sub-second updates. Estuary also supports automatic schema evolution and transformations using SQL, Python, and TypeScript.

If you’ve ever woken up to a broken data pipeline because of a deleted column, then you know the benefit of scheme evolution.

The platform can be deployed through Estuary’s public SaaS offering, a private deployment, or a Bring Your Own Cloud model. Private deployments allow the data plane to run inside the customer’s cloud environment or private network while Estuary manages the control plane. This may make Estuary more appealing to organizations with strict security, data residency, or compliance requirements.

Estuary also introduced Agent Skills in 2026, which allow teams to create, monitor, and troubleshoot pipelines from supported AI coding assistants. For example, a developer can ask an assistant to configure a PostgreSQL capture or materialize data into Snowflake, while still reviewing and approving the resulting configuration before it runs.

I’ve been working with Estuary for several years now as I am also an advisor for them.

CData Alternative #2: Portable

Portable is a cloud-based ELT platform that helps organizations load data from APIs, files, databases, and business applications into data warehouses and data lakes. The company focuses maily on long-tail business applications that may not be supported by larger data integration platforms. Currently they advertises more than 1,500 connectors.

Portable supports destinations such as Snowflake, Amazon Redshift, Google BigQuery, ClickHouse, PostgreSQL, and MySQL. It also supports data lakes and Databricks through file-based destinations such as Amazon S3, Azure Blob Storage, and Google Cloud Storage.

One potential benefit of Portable is its predictable pricing model. Rather than charging based on rows or data volume, Portable charges based on the number of enabled data flows. Its Standard plan currently starts at $1,800 per month for six enabled data flows and includes unlimited data volumes, hourly synchronization, and incremental loading.

However, Portable focuses primarily on extracting and loading data rather than transformation. Organizations will generally need another tool, such as dbt or SQL, to transform the data after it reaches the destination. Portable also currently limits its service to customers based in the United States. As a result, Portable may be a good CData alternative for U.S.-based organizations that need managed connectors for niche or less commonly supported business applications.

CData Alternative #3: Qlik Talend Data

Talend is now part of Qlik, which offers data integration tools through Qlik Talend, including Talend Studio and Talend Data Fabric. The company previously had an open-source version, Talend Open Studio. This was discontinued in 2024. Qlik Talend supports both ELT and ETL workloads and can be deployed in the cloud, on-premises, or in hybrid environments, making it a flexible and versatile choice.

According to G2 verified reviews of Talend Cloud Data Integration, the software’s ease of use and data integration capabilities are benefits of the platform. One potential downside is the cost. Qlik does not publish a simple per-user price for all Talend products, so prospective customers may need to contact the company for pricing based on their deployment and requirements.

CData Alternative #4: DLT

Another option for teams that prefer a code-first approach is dlt, or data load tool. dlt is an open-source Python library for extracting data from APIs, databases, cloud storage, files, and Python data structures and loading it into databases, data warehouses, data lakes, and other destinations.

dlt automates tasks such as schema inference, data normalization, incremental loading, schema evolution, and pipeline state management. Because it runs anywhere Python runs, teams can deploy dlt pipelines through tools such as Airflow, serverless functions, containers, or their existing cloud infrastructure.

Unlike CData, Portable, and other managed connector platforms, dlt generally requires users to write and maintain Python code. This gives engineering teams more control and flexibility, but it also means they are responsible for deploying, scheduling, monitoring, and supporting their pipelines. dltHub also offers a managed platform for teams that want deployment, observability, data quality, and collaboration capabilities around their dlt pipelines.

Other Options for CData Alternatives

Besides the three options above, there are other CData alternatives depending on your organization’s specific needs. For example, users interested in open-source software may prefer Apache NiFi, a data integration tool from the open-source Apache Software Foundation for building and managing dataflows. It has a user-friendly drag-and-drop interface, an extensible architecture, and support for scalable data routing, transformation, and system mediation.

On the other hand, you may prefer an option like Microsoft SQL Server Integration Services (SSIS), a platform for building enterprise-level data integration and data transformation solutions. While it’s older than the three options above, SSIS remains a viable option for organizations invested in SQL Server and the broader Microsoft ecosystem.

How to Choose the Right CData Alternative

With so many possible CData alternatives on your plate, how can you choose the right one from among the available data integration tools? Below are a few steps to follow:

Assess your business needs: Consider your organization’s goals and requirements both now and in the future, and evaluate how your choice of data integration tool can help meet these needs.

Run a pilot test: Prioritize data integration tools that offer a demo, free trial, or free tier so that you can test them out for yourself before moving to a full implementation.

Ensure a smooth implementation: Break the migration process into manageable phases, such as setup, testing, training, and monitoring, and define the timelines and resources allocated to each phase.

Conclusion

While CData is a well-established data integration and connectivity solution, it’s not ideal for every organization. Factors such as connector availability, deployment options, and cost may cause businesses to evaluate various CData alternatives, such as:

• Estuary, which performs real-time and batch data integration, ETL, and change data capture.
• Fivetran, which offers a large catalog of fully managed connectors but uses consumption-based pricing that can become expensive depending on the workload.
• Qlik Talend, a flexible solution that supports cloud, on-premises, and hybrid environments.
• Apache NiFi, an open-source option for users with more technical skills.
• Microsoft SSIS, which is a classic, especially for Microsoft shop(and then of course there is ADF)

For the next steps in exploring CData alternatives, start your research on the vendors’ websites and see what independent third-party reviews have to say on websites like G2 and Capterra. Once you’ve narrowed down your options, then you can get in touch with the software vendors’. And always look for free trials.

Also! Don’t forget to check the articles below.

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