10 Best Panoply Alternatives to Consider in 2025

Panoply is often a common choice for data integration and ETL workflows. It’s simple and cloud-based, but is it the right long-term fit for your data requirements?

Many teams find Panoply’s combined warehouse-ETL limiting, some dislike its lack of real-time syncs, and others think the pricing model is confusing.

If you relate to any of these difficulties, this article will help you.

We will cover the best Panoply alternatives that offer better flexibility, transparent pricing, advanced features, and stronger performance — helping you compare the top 10 tools by features, pros, cons, and pricing to find the right data integration solution for your business.

What Is Panoply?

Panoply is a data platform that combines a cloud data warehouse with built-in ELT capabilities to create a fully managed data pipeline. It helps you consolidate and analyze data from multiple sources without managing separate infrastructure. You can load data into a managed warehouse and run SQL queries or connect BI tools for insights.

Panoply offers pre-built connectors for popular SaaS applications and databases, supporting automated data syncs on a schedule. Its ELT architecture loads raw data first and transforms it on demand for analysis.

It is ideal for small to mid-sized teams seeking ease of use, minimal maintenance, and fast access to actionable insights.

Why Are People Moving Away from Panoply?

Although Panoply is a useful tool for many, it has some drawbacks that compel users to switch to other tools.

1. Limited warehouse flexibility

Panoply operates as a fully managed environment built on cloud data warehouses such as Redshift and BigQuery. You can’t connect it to your existing data warehouse or regulate warehouse-level configurations.

Teams already using Snowflake, their own BigQuery, or Redshift must maintain dual setups or migrate fully to Panoply’s managed instance. This can increase operational overhead, hence often driving customers away.

What do you dislike about Panoply? My only real dislike is the friction in automating the process of importing BigQuery data into Google Sheets. Since the BigQuery account is provisioned by Panoply, it cannot directly connect to a Sheet, which would be nice to be able to take advantage of the native Sheets BigQuery integration. As a workaround, I\'ve been using another add-on to query the database and import results into Sheets. However, it would be nice to be able to use the native Sheets/BigQuery features for a more streamlined workflow.

Chance R.

View Review

2. Batch processing constraints

The platform’s default minimum sync frequency of 10 minutes doesn’t support businesses that need real-time data movement. Modern analytics often require sub-minute latency for operational dashboards and customer-facing applications. As data volumes and refresh frequency increase, the reliance on batch-only processing becomes a significant latency challenge for the big data pipeline.

The web UI/UX needs more work, it can be slow, and there are many features that are only available on request from the backend (history tables, ssh tunnel for connections, etc.). The replication frequency is rather limited (down to 1hr only), and the lack of change log replication is a big cons (e.g. MongoDB chagelog or Postgres replication log).

Verified Reviewer

View Review

3. Pricing opacity

Users often report limited visibility into how storage, query usage, or data volume translates to costs. The platform’s bundled model combines ETL, storage, and compute, making it difficult to separate and optimize spending as usage grows. This leads to unexpected cost variations in charges.

Could be the pricing model, we noticed that another tools like airbyte or another open source could be more cheaper than panoply in any aspects, this one of the reason I dislike panoply

Enrique L.

Data Architect

View Review

4. Feature gaps for advanced users

Panoply’s core appeal lies in automation and ease of use, but it lacks advanced features. Users looking for granular transformation management, schema evolution control, or integration with orchestration tools like Airflow or dbt often find the environment limiting.

If you aim to evolve from basic reporting to more mature data operations, such as predictive modeling, multi-source lineage tracking, or reverse ETL, Panoply’s capabilities might seem limited. This pushes many teams to switch to platforms that provide deeper customization and scalability.

What do you dislike about Panoply? Help: Support times are rather long Reporting: Little insights in the interface about the product usage Making the reporting processes more transparent would help customers to get engaged in the product even more.

Sevda H.

Lead Data Analyst

View Review

Top 10 Panoply Alternatives to Consider

Choosing the right alternative to Panoply depends on your specific requirements. The platforms below represent the best options across different use cases and team sizes.

1. Hevo

G2 rating: 4.4 (271)

Hevo delivers a fully managed no-code ETL and ELT platform that unifies data from over 150 pre-built sources to your preferred data warehouse. It automates the entire pipeline lifecycle and keeps data accurate and up-to-date for stakeholders.

Hevo ensures real-time data flow and automatic scaling. This makes it an ideal choice for growing startups and mid-market businesses seeking simplicity, flexibility, and performance in their data operations.

Key features

• Advanced transformations: Supports SQL-based modeling, event-based transformations, and integration with dbt for complex workflows.
• DevOps-ready pipelines: Provides CI/CD and API-driven management to simplify deployment, version control, and integration across multiple environments.
• Custom connectors: Offers connections to unique or niche data sources beyond pre-built integrations, available upon request or through custom code.
• Observability dashboards: Delivers real-time monitoring and visual insights into pipeline health, errors, and performance for proactive management.

Pros

• Enterprise-grade compliance.
• Robust customer support for all users.
• Predictable and competitive pricing.

Cons

• Doesn’t offer on-premise support.
• Complex transformations may require technical expertise.
• Limited flexibility compared to open-source options.

Pricing

Hevo offers a simple usage-based pricing model.

• Free: Covers up to 1 million events monthly and supports five users.
• Starter: From $239/month, includes 50 million events with SSH/SSL security for 10 users.
• Professional: From $679/month, supports 100 million events with reverse SSH and unlimited users.
• Business Critical: Custom pricing for workloads above 100 million events.

It also offers a free 14-day trial.

Why should you choose Hevo over Panoply?

Choose Hevo if you need a reliable integration engine rather than a combined warehouse tool. It scales effortlessly as your data grows and offers the perfect balance of no-code simplicity and flexible customization that Panoply lacks.

What do you dislike about Panoply? My only real dislike is the friction in automating the process of importing BigQuery data into Google Sheets. Since the BigQuery account is provisioned by Panoply, it cannot directly connect to a Sheet, which would be nice to be able to take advantage of the native Sheets BigQuery integration. As a workaround, I\'ve been using another add-on to query the database and import results into Sheets. However, it would be nice to be able to use the native Sheets/BigQuery features for a more streamlined workflow.

Chance R.

View Review

Read the full case study here.

2. Airbyte

G2 rating: 4.4 (65)

Airbyte is a free and open-source data integration platform built for flexibility and full autonomy. It gives you access to over 600 pre-built connectors for APIs, databases, and files.

Its modular design makes it a strong choice for those who want customization more than bundled platforms like Panoply. Airbyte’s developer-first approach and support for emerging data stores like vector databases make it a scalable, cost-effective, and extensible alternative for your data needs.

Key features

• Connector Development Kit (CDK): Offers a Python framework that simplifies building custom connectors for proprietary or niche systems.
• Complex transformations: Integrates with dbt for handling transformations after data loads into your warehouse.
• Containerized architecture: Built on a Kubernetes-native framework where each sync runs in an isolated container to prevent pipeline failures. 
• Schema management: Maintains advanced schema handling to ensure consistency and adapt to evolving datasets.

Pros

• Offers cloud, on-premise, and hybrid setups.
• Full separation of control and data planes.
• No vendor lock-in with the self-hosted model.

Cons

• Requires technical expertise to set up and maintain pipelines.
• Limited built-in analytics or visualization capabilities.
• High memory requirements for self-hosted deployments.

Pricing

Aibyte offers pricing options for different user requirements. The Core plan is free for self-hosted deployments, while the fully managed Cloud Standard plan starts at $10/month.

Business and Enterprise tiers provide scalable hosting choices and enhanced governance at a custom price. A 14-day free trial is available.

Why should you choose Airbyte over Panoply?

Airbyte is known for its active open-source community that constantly updates and contributes improvements. You can adapt, extend, and troubleshoot pipelines in ways Panoply cannot.

Customer review

I really appreciate that Airbyte is open-source and comes with a wide range of pre-built connectors. The UI is intuitive, and the platform makes it easy to configure data syncs. I also like how frequently updates and improvements are made by the team and the community.

Aniruddh S.

Indigo Squad Member

3. Fivetran

G2 rating: 4.2 (445)

Fivetran is a fully managed ELT platform that automates data movement across systems. With over 700 secure connectors, it effortlessly integrates data from SaaS apps, databases, and files into your warehouse or data lake.

It is ideal for enterprises handling large-scale analytics or AI workloads. Fivetran handles schema changes and connector updates automatically, offering a truly maintenance-free experience.

Key features

• ERP and system replication: Extracts and synchronizes complex data from large systems, such as Oracle, SAP ERP, and NetSuite, for unified enterprise reporting. 
• Reverse ETL: Transfers transformed warehouse data back into operational systems, CRMs, and business applications for actionable insights.
• Security management: Includes data blocking and column hashing to safeguard sensitive fields and meet compliance requirements across industries.
• Data lineage visibility: Tracks every data movement from source to destination for complete transparency into dependencies and historical changes.

Pros

• 99.9% service level guarantee on platform uptime.
• Continuous data quality monitoring and automatic error handling.
• Auto-updates for connectors on SaaS API changes.

Cons

• Offers 1-minute syncs only in higher-tier plans.
• Limited transformation flexibility compared to warehouse-native tools.
• Unpredictable pricing.

Pricing

Fivetran bills according to Monthly Active Rows (MARs) for each connection. Its free tier includes 500,000 MARs and 5,000 model runs monthly. Paid subscriptions begin at $500 per million MARs and come with a 14-day free trial period.

Why should you choose Fivetran over Panoply?

Choose Fivetran if you want unmatched stability and depth for large volume data, and manage near-time syncs. It separates connector management from storage infrastructure. It is the ideal tool when you need to free up your engineering resources but ensure enterprise-level governance.

Customer review

I appreciate Fivetran\'s ease of setup and usage, which made integrating our systems straightforward. Its reliability and secure platform ensure smooth data synchronization across multiple databases. I value its robust networking capabilities and the helpful services it provides for SaaS applications. Additionally, it simplifies schema management with its flexible features and supports enhanced data delivery and performance.

Navitha C.

Java Software Engineer

4. Rivery

G2 rating: 4.7 (120)

Rivery is a cloud-native platform that combines data ingestion, transformation, and complex workflow orchestration into a unified solution. It enables you to build end-to-end data pipelines for modern data warehouses and data lakes with 200+ connectors.

You can automate your entire data workflow and move beyond simple replication to manage complex workflows with conditional logic, multi-step dependencies, and data activation.

Key features

• DataOps management: Centralizes authority over data pipelines, monitoring, and testing for consistent operations.
• Reverse ETL capabilities: Enable sending processed warehouse data back to operational systems and applications.
• Starter kits: Offers ready-to-use templates for common data workflows to speed up setup and implementation.
• Dynamic parameterization: Allows pipelines to adjust automatically based on variable inputs, schedules, or external conditions for flexibility.

Pros

• Offers a low-code custom API connector tool.
• Multi-environment support with easy promotion between stages.
• Git-based version control enables team collaboration and rollback capabilities.

Cons

• It can be expensive for smaller teams.
• Steeper learning curve for complex pipelines and advanced features.
• No support for on-premise deployment.

Pricing

Rivery charges based on Boomi Data Units (BDU), starting at $0.90 per credit. Custom pricing is available for larger-scale plans and enterprise requirements.

Why should you choose Rivery over Panoply?

Rivery provides flexibility and autonomy over data workflows. It lets your team automate pipelines, adjust to dynamic inputs, and synchronize data across systems. This offers better scalability in the long run.

Customer review

Using Rivery for marketing APIs has really streamlined the process of pulling data from multiple marketing platforms and centralizing it for analysis and reporting. By far the best thing about my own experience with Rivery has been the attentititve customer support, clear onboarding/suppotr process, and regular check ins.

Harry C.

Data Analyst

5. Polytomic

G2 rating: 4.8 (46)

Polytomic offers a unified platform for ETL, reverse ETL, and Change Data Capture (CDC). It is built for data, marketing, and revenue teams that want to activate warehouse data directly in operational apps like Salesforce or HubSpot.

Polytomic replaces multiple vendors and simplifies complex data movement across diverse systems. It also offers capabilities like self-hosting for private cloud deployment, which is a key differentiator from most cloud-only alternatives.

Key features

• IaC-ready deployment: Enables defining and provisioning all pipeline configurations declaratively using Infrastructure as Code for tools like Terraform.
• Flexible transformations: Provides both no-code and SQL-based transformations for regulation over how data is modeled.
• Access and auditing: Offers role-based access controls (RBAC) and audit logs to secure pipelines and track all user actions.
• Developer-friendly API: Delivers a first-class API with native SDKs in languages like Python and TypeScript for easy integration and automation.

Pros

• Highly responsive customer support.
• Enterprise-grade compliance, including SOC 2, GDPR, and HIPAA.
• Fault-tolerant architecture ensures reliable data delivery.

Cons

• Pricing may be high for smaller teams.
• Limited pre-built analytics or visualization tools.
• It has a learning curve for complex workflows.

Pricing

Polytomic offers custom pricing for standard and enterprise plans starting at $500/month.

Why should you choose Polytomic over Panoply?

Polytomic empowers RevOps and marketing teams with reverse ETL, syncing warehouse customer segments directly to Salesforce, HubSpot, and ad platforms. Unlike Panoply, Polytomic supports private cloud deployment for teams requiring data residency compliance.

Customer review

We use Polytomic for CDC-based Postgres to Snowflake replication, and it has been consistently smooth and reliable. Their support team is exceptional (and I really mean exceptional) - highly responsive and very knowledgeable whenever we’ve had questions. The UI is clear and easy to use, and their service has proven robust in day-to-day operations. We benchmarked Polytomic against other competitors during trial, and it stood out immediately as the more reliable and well-thought-out solution.

Arash T.

Senior Data Engineer

View Review

6. Dataddo

G2 rating: 4.7 (184)

Dataddo specializes in flexible support for ETL, ELT, reverse ETL, and replication. It is ideal for business users and analysts who prioritize connecting marketing and operational applications directly to their dashboards.

This fully managed service automates transfers from over 300 sources to a chosen destination in near real-time, and helps you achieve self-service analytics. This approach reduces dependency on internal data engineering teams.

Key features

• Multi-tenant scalability: Provides a high-performance architecture that handles multiple accounts and large data volumes without slowing down workflows.
• Rapid custom connectors: Offers new connectors on request within 10 days to meet unique integration requirements quickly.
• Data quality firewall: Ensures all incoming data meets validation rules before entering pipelines to prevent errors downstream.
• Flexible data blending: Combines, joins, and unifies datasets from multiple sources for richer analytics and reporting.

Pros

• Sends data directly to dashboarding tools, not just warehouses.
• Strong data governance with 16 data processing locations.
• Full REST API for Headless Data Integration and developer customization.

Cons

• Pricing can increase with high data volumes.
• Users report reliability and performance issues when handling a huge scale.
• Complex transformations require external SQL tools or scripting.

Pricing

Dataddo offers subscription-based pricing starting with a free plan for three weekly workflows. Paid plans start at $129/month with more frequent syncs. A 14-day free trial is available.

Why should you choose Dataddo over Panoply?

Dataddo outperforms Panoply by focusing on direct cloud-to-cloud data movement instead of bundling storage and ETL. Its optimized dashboard-first workflow bypasses Panoply’s warehouse-centric model. This reduces latency and simplifies analytics for faster and more actionable insights.

Customer review

I highly recommend Dataddo\'s data integration platform. Dataddo impressess me with its ability to provide a single location for all our integrations from various saas services and we no longer have to worry about managing everything individually. We are also starting to experiment with reverse ETL to leverage more data insight.

Verified User

Human Resources

7. Stitch

G2 rating: 4.9 (79)

Stitch, now owned by Talend, is an ELT platform that replicates raw data from 130+ sources into cloud warehouses like Snowflake or Redshift. It gives you a view of your storage and transformations. It focuses primarily on data replication and uses the open-source Singer framework for extensible connectors.

Stitch’s developer-centric approach, straightforward volume-based pricing, and generous free trial make it ideal for organizations with in-house technical expertise.

Key features

• Custom replication engine: Lets you configure how and when data is replicated to match your workflow needs.
• Enterprise security: Secures data with SSH tunneling, encryption, and advanced protection during transit and at rest.
• Extract-only design: Delivers raw data without enforced transformations for complete autonomy over processing.
• Multi-destination support: Sends data to several cloud warehouses simultaneously for redundancy or parallel analytics.

Pros

• Offers ready-to-query schemas.
• Supports full historical syncs.
• Provides a REST API for custom data injection.

Cons

• Lacks on-premise deployment options.
• Limited built-in transformation features.
• Limited support when community connectors face issues.

Pricing

Stitch uses a subscription-based pricing model with a 14-day free trial. The Standard plan starts at $100 per month for 5 million rows. Advanced and Premium plans scale to 100 million and 1 billion rows, respectively, with custom pricing.

Why should you choose Stitch over Panoply?

Stitch works best for teams that already have a data warehouse and want precise replication. Unlike Panoply, it saves you unnecessary costs by giving you the flexibility to move data where you need it.

Customer review

Stitch is an easy tool to include ETL from sources into your data warehouse. Set up is really easy to do, and its low maintenance, which helps in small data teams.

Verified User

8. Matillion

G2 rating: 4.4 (81)

Matillion is a multi-cloud ETL and ELT platform that enables you to design and orchestrate complex pipelines. It uses a visual interface or code options like Python and dbt, and emphasizes advanced data transformation over storage.

The platform uses pushdown processing, executing transformations directly within the cloud data warehouse itself for superior performance and reduced latency. This integrated approach saves time and optimizes compute resources.

Key features

• API-first architecture: Enables programmatic automation and precise autonomy over complex pipelines and workflows for integration with external tools and processes.
• Reverse ETL support: Allows organizations to send transformed analytical data from a warehouse back to business applications and turn insights into actions.
• Git-based version control: Provides built-in Git integration for change tracking, collaboration, and rollback, to ensure consistent and auditable data pipeline management.
• Multi-cloud connectivity: Supports leading warehouses across AWS, Azure, and Google Cloud, giving teams the flexibility to deploy and scale data operations in any environment.

Pros

• Native AI and ML integrations like Copilot AI for pipeline optimization.
• Strong customer support with up to 1-hour response times.
• Offers detailed job monitoring and audit history for governance requirements.

Cons

• Beginners may face a steep learning curve with advanced features.
• Cost can escalate quickly with high consumption.
• The visual interface can lag with large projects.

Pricing

Matillion’s pricing is based on vCore hours used, starting at $2.50 per credit for the Developer plan. Higher-tier plans require a minimum monthly commitment and custom quotes. A 14-day free trial is available.

Why should you choose Matillion over Panoply?

Matillion is better than Panoply due to its focus on complex, cloud-native ELT transformation using the power of your data warehouse. While Panoply is better suited for basic data loading, Matillion offers deeper authority and scalability.

Customer review

What I like best about Matillion is its seamless integration with major cloud platforms like AWS, GCP and Azure. This is very user friendly platform for ETL. It\'s visual interface makes complex workflows look easier. It offers great scalability, making it suitable for big and small scale users. It helps to reduce the complexity of ETL Process with its no code working ability.

Nikhil L.

Data Engineer

9. Integrate.io

G2 rating: 4.3 (208)

Integrate.io, formerly Xplenty, is a low-code ETL and reverse ETL platform for technical and non-technical users. The service includes 200+ native connectors covering SaaS applications, databases, and APIs.

Its fixed-fee pricing and multi-cloud deployment make it accessible for SMBs and regulated industries needing compliance and cost predictability.

Key features

• Multi-cloud data handling: Provides connectivity and flexible data residency options across AWS, Azure, and Google Cloud for better performance.
• Team collaboration tools: Enable teams to coordinate and track changes in pipelines without conflicts.
• Universal REST API connector: Connects any REST API directly to your pipelines to unify and enrich disparate datasets.
• Historical data backfill: Populates warehouses with past data to ensure analytics and reporting capture complete trends.

Pros

• Offers HIPAA, SOC 2, and GDPR standards for regulated industries.
• 24/7 customer support for all users.
• Provides real-time alerts and operational visibility across pipelines.

Cons

• It might be expensive for smaller teams.
• No native BI or visualization tools.
• Some complex integrations require technical expertise to configure.

Pricing

Integrate.io offers a predictable pricing structure with a 14-day trial. The Core plan starts at $1,999 per month, and enterprise customers can request customized plans tailored to their specific needs.

Why should you choose Integrate.io over Panoply?

Integrate.io offers the perfect middle ground. It provides more control than Panoply’s all-in-one model, but less technical overhead than open-source alternatives. Choose it for full flexibility in data residency and predictable, flat-rate operational costs.

Customer review

The ease of use and flexibility of the platform, allowing for any source, any transformation, and any destination. The team at Integrate.io is extremely knowledgeable about the product and very responsive in customer support.

Alejandro F.

Information Technology Business Analyst

10. Airflow

G2 rating: 4.4 (113)

Apache Airflow is a programmable platform for creating, scheduling, and monitoring workflows entirely in Python. It allows you to define data movement and transformation with dynamic pipelines.

Airflow offers an extensible framework where teams deploy custom logic and connect seamlessly with cloud providers like AWS and Google Cloud.

Key features

• Comprehensive logging: Provides complete task-level logs, SLA alerts, and dashboards for full operational transparency.
• Conditional task flow: Enables precise execution order, branching, and retry logic across complex workflows.
• High-performance engine: Handles thousands of concurrent tasks using Celery, Kubernetes, or LocalExecutor for scalable execution.
• Data-aware scheduling: Supports OpenLineage to track data dependencies, provenance, and workflow lineage across pipelines.

Pros

• Open-source and free with no licensing costs.
• Strong community support and active development.
• Scheduler handles complex historical data backfills efficiently.

Cons

• Requires a team exclusively proficient in Python.
• Initial setup and maintenance complexity are high.
• Not optimized for real-time or streaming data processing.

Pricing

Airflow is free, but charges for underlying management workflows, such as Amazon Managed Workflows for Apache Airflow (MWAA) and Google Cloud Composer.

Why should you choose Airflow over Panoply?

Airflow provides architectural transparency that Panoply struggles to match. You can inspect and debug any aspect of your workflow at the code level. This is essential if you are managing mission-critical pipelines where understanding what’s happening matters more than turnkey simplicity.

Customer review

The best thing about Apache Airflow is that it provides integration with various services like big query , AWS , GCP etc.Plus it is available as as service in all cloud provides which provides seamless experience.The User Experience is perfect.

Ashutosh R.

Data Engineer

What Factors Should You Consider When Choosing a Panoply Alternative?

Each tool has different strengths, and the right fit depends on how your team manages data. Before switching to a new data integration platform, here’s what to consider. 

1. Technical resources

If your team has limited engineering bandwidth, choose a no-code or low-code data pipeline tool that automates setup, monitoring, and pipeline management. However, if you have in-house data engineers or want to invest in a team, open-source platforms might be more suitable. They give you greater authority over configurations, transformations, and versioning.

2. Integration requirements

List all your data sources, destinations, and the frequency of data movement. If you rely heavily on SaaS tools, look for platforms that offer pre-built connectors and automated schema handling. For hybrid environments with on-premise databases or custom APIs, prioritize tools that support custom connectors or API-based integration to ensure flexibility.

3. Transformation needs

Evaluate whether your workflow requires pre-load transformations or post-load transformations. Ensure the platform supports complex logic scheduling and dependency management for pre-load transformations. Look for ETL tools that integrate easily with other platforms like dbt or support SQL-based modeling to avoid any friction in the future.

4. Budget plan

Some tools charge based on data volume or credits, while others use flat or tier-based pricing. If your budget is limited and you want predictability, prioritize transparent pricing structures where ETL, storage, and compute costs are clearly separated. Larger teams should consider enterprise plans that include monitoring, support, and SLA guarantees.

5. Scalability and performance

Your data needs might be small today, but scalability is key for long-term value. Choose a platform that supports real-time or near real-time syncs, handles large data volumes efficiently, and scales storage and compute independently. Also, review how well it manages concurrent pipelines and data freshness at scale.

Why Should You Choose Hevo?

Hevo offers what Panoply lacks, such as real-time data syncs, scalability, transparent usage-based pricing, and much more.

Apart from the existing 150 connectors, Hevo provides custom and on-demand connectors for unique data sources. It combines a no-code interface with advanced scripting, API support, and automation features to simplify even the most demanding data workflows.

Flexible integrations with cloud and on-premise warehouses eliminate vendor lock-in, while an intuitive interface minimizes setup time.

Built for compliance with GDPR, HIPAA, CCPA, and SOC 2 Type 2, Hevo supports data security. This makes it a scalable, reliable, and future-ready data platform.

Want to try it for yourself? Book a free demo today!

FAQs