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Fivetran vs Stitch: In-Depth ETL Tool Comparison 2024

Save yourself time weighing the pros and cons of top ETL tools. Compare Fivetran vs Stitch side by side: price, features, learning curve, and more.

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As data becomes the foundation of success for so many businesses, the requirement for data literacy—and tools like Fivetran vs Stitch—becomes ever greater within organizations of all sizes. However, it's not feasible for every business to employ a large team of data engineers to build a state-of-the-art data platform with custom pipelines, connectors, and software to support the entire infrastructure.

Fortunately, emerging data integration platforms offer managed services for businesses that lack internal expertise. These platforms simplify the creation of foundational ETL pipelines, enabling companies to combine data from various sources into a unified repository, such as a data warehouse or data lake.

Two of the leaders in this industry are Stitch and Fivetran. These platforms provide robust features that can help businesses of all sizes ingest data into a usable format, delivering quick value back to the organization without the need for in-house expertise.

In this article, I’ll compare and contrast these two tools—Fivetran vs Stitch—to help you determine which one will best elevate your ETL capabilities.

If you're interested in directly comparing Fivetran, Stitch, and Estuary Flow across key features, skip ahead to the detailed comparison tables by clicking here.

Stitch: Zero Maintenance Data Pipelines

fivetran vs stitch - stitch logo

Stitch is a SaaS-based batch ELT tool, initially developed from the Singer open-source project within RJMetrics. After Magento acquired RJMetrics in 2016, Stitch spun off as an independent company. In 2017, Stitch contributed to the Singer open-source project, and by 2018, it was acquired by Talend. Today, Stitch serves over 3,000 companies, with many more leveraging the Singer framework.

Despite being branded as ETL, Stitch operates as a batch ELT tool, performing basic data conversions to move raw data from each source to the target—similar to most other ELT technologies. However, like many other vendors, Stitch only supports soft deletes.

Stitch: Key Features and Benefits

  • Open Source: Stitch’s foundation on the Singer framework provides robust open-source support. Multiple platforms, including Stitch, Meltano, Airbyte, and Estuary, can support Singer taps, offering users flexibility in their data integration projects.
  • Log Retention: Stitch offers up to 60 days of log retention, a feature that outperforms many competitors other than Estuary, which can store indefinitely. The data is stored encrypted, but in a Stitch account.
  • Qlik Integration: For existing Qlik customers, Stitch’s integration with other Qlik products makes it an attractive choice, offering seamless data integration across platforms.

Stitch: Potential Downsides

  • Lack of Innovation: Since Talend’s acquisition by Qlik, innovation in Stitch and the Singer framework has slowed down, with other platforms like Meltano investing more in the Singer project.
  • Batch only: Despite the fact that Stitch can store data in transit, it doesn’t support any real-time. It is batch only with a minimum 30 minute interval.
  • Limited load options: Stitch supports soft deletes, not hard deletes. It also supports append only writes with at least once delivery. If you want to dedup or create a current view you’ll need to do that within the destination.
  • Limited scalability: Stitch (cloud) only supports 1 connector running at a time. If the current connector does not finish in time for the next scheduled connector, the next connector job is skipped. 
  • Limited Connectors: Stitch supports just over 140 sources and 11 destinations, which, while significant, lags behind other platforms.
  • Limited DataOps: Stitch does not support any automation for schema drift and evolution. Many changes will stop the pipeline. While there is an admin API, there is no CLI to support automation.
  • Pricing: Stitch’s pricing can escalate quickly. A reasonable deployment often costs $1250+ per month, with higher tiers like Premium starting at $2500 per month.
  • Support: While Qlik provides dedicated support for Stitch, there are mixed reviews about Stitch the last few years. Once things go wrong, they can take a while to resolve.

Stitch: Pricing Overview

  • Basic Plan: $100 per month or $1000 per year, supporting up to 3 million rows per month.
  • Advanced Plan: $1250 per month, supporting up to 100 million rows per month.
  • Premium Plan: $2500 per month, supporting up to 1 billion rows per month
Fivetran vs Stitch
Fivetran vs Stitch vs Estuary Flow

Fivetran: The Fancy Swiss Army Knife of ELT

fivetran vs stitch - fivetran logo

Fivetran, founded in 2012 by George Fraser and Taylor Brown, emerged as a Y Combinator-backed startup with a mission to streamline and simplify integration and analytics. But after a few years Fivetran focused on just data integration because that’s what customers wanted. In 2020 Fivetran added dbt core and CDC support.

Fivetran has become an easy-to-use, reliable, and scalable ELT tool with one of the widest ranges of connectivity.

Fivetran: Key Features and Benefits

  • Ease of use: Fivetran is an easy-to-use tool. Beyond its relatively easy connectivity, it has added integration with dbtcore that makes adding transformations straightforward.
  • Connectivity: Fivetran has nearly 300 pre-built connectors to databases, SaaS apps, software infrastructure, and data warehouses, as well as another 300+ “lite” connectors that call APIs to various apps and systems.
  • Write options: Fivetran does support soft and hard deletes, and append-only and update-in-place writes.
  • Scalability: Fivetran scales better than most other ELT tools.
  • Schema evolution: Fivetran has strong support for schema evolution, which minimizes disruptions in data pipelines.

Fivetran: Potential Downsides

  • Limited Transformation Capabilities: Like Stitch, Fivetran focuses on the Extract and Load parts of ELT, and relies on dbtcore for transformations. There is no support for ETL.
  • Pricing Transparency: Fivetran’s consumption-based pricing model can be difficult to estimate, with potential cost variability making it challenging for smaller businesses to budget effectively.
  • Latency: Like Stitch, Fivetran is also batch ELT. Its latency varies by plan: Enterprise is 15 minutes of minimum latency, Business critical is 1 minute of min latency, but costs more than 2x the standard edition, and in reality is almost never deployed with its minimum latency.
  • Costs: Fivetran is the most expensive ELT vendor according to many. Its monthly active rows (MAR) are based on Fivetran’s internal representation of your data, not your source rows. For some sources, Fivetran can only download all data each time. For non-relational sources, Fivetran converts data into highly normalized relational data. Both make costs soar.
  • Reliability: While Fivetran is more reliable than most other ELT vendors, it still has some reliability issues. Some customers complain about receiving and having to handle alerts. Fivetran even had a 2.5 day outage in 2022. Fivetran’s current SLA has an allowed downtime interval of 12 hours before downtime SLAs start to go into effect. They also do not include any downtime from their cloud provider.
  • Deployment options: While you can self-host HVR, and there is an option to deploy 5 sources and 4 destinations as part of a private deployment, Fivetran is really public cloud only. 
  • Support: Some customers also mention Fivetran support can be slow to respond.
  • DataOps: Fivetran does not provide much control or transparency into how they change field names and data structures, and you can’t rename columns. They also don’t always bring in all the data depending on the data structure. 
  • Roadmap: Fivetran doesn’t show much of a roadmap.

Fivetran Pricing Overview

Fivetran’s pricing is based on monthly active rows (MAR) that change at least once a month. MARs are based on Fivetran’s internal representation of your data. It does not change relational sources much beyond column naming changes. But Fivetran does download all data for some sources each time, and highly normalized non-relational sources. Both can dramatically increase your MAR counts. 

Pricing starts at $900 per million MAR and slowly declines in costs. But this can easily lead to 5x the cost of several other ELT options.

Estuary Flow: Real-Time and Batch ELT/ETL

fivetran vs stitch - estuary logo

Estuary was founded in 2019. Its core technology, the Gazette open source project, has been used for a decade within Ad Tech. 

Estuary Flow supports real-time and batch ETL and ELT. It has several strengths. It is one of the best change data capture (CDC) technologies on the market today, combines real-time and batch, and can load multiple destinations in the same pipeline.

This is made possible by Flow’s unique architecture which streams and stores data (called collections) using transactionally guaranteed exactly once delivery from each source a collection, and each collection to a target. For example, with CDC each change is captured exactly once in real-time and can be loaded into multiple targets in real-time or batch. 

Estuary Flow: Key Features and Benefits

  • Ease of use: Flow is one of the easiest to use tools. Most customers are able to get their first pipelines running in hours. Many have been able to improve productivity 4x over time.
  • Modern transforms: Flow is also both low-code and code-friendly with support for SQL and TypeScript for (real-time) ETL, and dbt for ELT.
  • Lowest latency: Flow is the only real-time ELT and ETL here, with sub-100ms latency.
  • High scale: Flow is proven to scale much higher, with one production pipeline moving 7GB+/sec, which is much larger than any known Stitch or Fivetran pipeline.
  • Most efficient: Flow is the only product with real-time CDC connectors. It also does exactly-and-only-once capture. If you need the same data second time for existing or new destinations, you get it from Flow, not the source.
  • Modern DataOps: Flow has the best support for schema drift, evolution, and automation, as well as a CLI and API for DataOps.
  • Deployment options: Flow is currently the only vendor to offer open source, private cloud, and public multi-tenant SaaS.
  • Reliability: Flow’s exactly-once transactional delivery, immediate streaming from the source, and durable stream storage improves reliability and availability.
  • Lowest cost: Estuary is the clear low-cost winner in this evaluation. Stitch and Fivetran both have higher pricing.
  • Great support: Users mention great support as one of the reasons they adopted Flow.

Estuary Flow: Potential Downsides

  • On premises connectors: Estuary has 150+ native connectors and supports 500+ Airbyte, Meltano, and Stitch open source connectors. If you need more open source connectivity, or the open source connectors aren’t good enough, you should talk to Estuary about your options and consider other options.
  • Graphical ETL: Estuary has been more focused on SQL and dbt than graphical transformations. While it does infer data types and convert between sources and targets, there is currently no graphical transformation UI.

Estuary Pricing

Of the various ELT vendors, Estuary is the lowest total cost option. 

Estuary only charges $0.50 per GB of data moved from each source or to each target and $100 per connector per month. So you can expect to pay a minimum of a few thousand per year. As you grow it quickly becomes the lowest cost pricing by a factor of 5x or more. 

Detailed Comparison Fivetran vs Stitch vs Estuary

What follows is the detailed comparison of Fivetran vs Stitch vs Estuary. It compares the vendors across nearly 40 categories:

Use Case Comparisons: Fivetran vs Stitch vs Estuary Flow

When evaluating ETL tools, understanding the specific use cases they support is crucial. This table breaks down how Fivetran, Stitch, and Estuary Flow handle core data integration scenarios, including CDC (Change Data Capture), data migration, and operational analytics.

Use Cases/ToolsFivetranStitchEstuary
Database replication (CDC) - sourcesNative MySQL, SQL Server, Postgres, Oracle (ELT load only) Single target only. Batch CDC only.MariaDB, MySQL, Oracle, Postgres, SQL Server (Batch)Native CDC for MySQL, SQL Server, Postgres, MongoDB, Firestore
Replication to ODSNo (batch CDC only)No (batch CDC only)Yes (real-time CDC)
Historical Analytics1 destination ELT1 destination ELTMany-to-many ELT/ETL
Op. data integrationNo (batch ELT only)No (batch ELT only)Yes (real-time ETL)
Data migrationNo (batch ELT only)No (batch ELT only)Yes (real-time ETL)
Stream processingNo (batch ELT only)No (batch ELT only)Yes (real-time ETL)
Operational AnalyticsHigher latency batch ELT onlyHigher latency batch ELT onlyStreaming ETL/ELT
Data science and MLELT onlyELT onlySQL, TypeScript support (Python Q2 2024)
AI PipelineNonePinecone (batch ELT only)None

Connector Availability and Flexibility: Fivetran vs Stitch vs Estuary Flow

The variety and performance of connectors are key differentiators in data integration platforms. This table outlines the number of connectors, support for third-party and custom connectors, and how each platform handles streaming connectors.

Connectors/ToolsFivetranStitchEstuary Flow
Number of connectors<300 connectors 300+ lite (API) connectors150+150+ high performance connectors built by Estuary
Streaming connectorsBatch CDC only. Batch Kafka & Kinesis both source only.NoneStreaming CDC, Kafka, Kinesis (source only)
Support for 3rd party connectorsNoNoneSupport for 500+ Airbyte, Stitch, and Meltano connectors
Custom SDKYes (custom function and hosted Lite connectors)Yes Import APIYes (adds new 3rd party connector support fast)
API (for admin)Yes Fivetran Rest API docsYes Stitch ConnectYes Estuary API docs

Core Features Comparison: Fivetran vs Stitch vs Estuary Flow

This table highlights key capabilities like batch and streaming support, transformation methods, delivery guarantees, and DataOps automation for Fivetran, Stitch, and Estuary Flow.

Core Features/ToolsFivetranStitchEstuary Flow
Batch and streamingBatch onlyBatch onlyStreaming to batch Batch to streaming
ETL TransformsNoneNoneSQL & TypeScript (Python Q124).
WorkflowNoneNoneMany-to-many pub-sub ETL
ELT transformsELT only with dbt (Python, SQL). Integrated orchestrationELT only with dbt in the destinationDbt. Integrated orchestration.
Delivery guaranteeExactly once (batch only)At least once (Singer-based)Exactly once (streaming, batch, mixed)
Load write methodAppend only or update in place (soft deletes)Append only (soft deletes)Append only or update in place (soft or hard deletes)
Store and replayNo storage. Requires new extract for each backfill or CDC restart.No storage. Requires new extract for each backfill or CDC restart.Yes. Can backfill multiple targets and times without requiring new extract.
Time travelNoNoYes
Schema inference and driftGood schema inference, automating schema evolutionNoGood schema inference, automating schema evolution
DataOps supportCLI,APIAPICLI, API, Built-in testing

Deployment, Performance, and Security: Fivetran vs Stitch vs Estuary Flow

This table compares Fivetran, Stitch, and Estuary Flow across these categories to help you assess which platform aligns with your infrastructure needs.

 FivetranStitchEstuary Flow
Deployment optionsCloud, limited private cloud (5 sources, 4 destinations), self-hosted HVROpen source (Singer), Stitch CloudOpen source, Public cloud, private cloud
Performance (minimum latency)Theoretically 15 minutes enterprise, 1 minute business critical. But most deployments are in the 10s of minutes to hour intervalsBatch by design with 30 minute minimum interval and increments. Only one job can run at a time (cloud)< 100 ms (in streaming mode) Supports any batch interval as well and can mix streaming and batch in 1 pipeline.
ScalabilityMedium-High
HVR is high scale
Low-mediumHigh
5-10x scalability of others in production
ReliabilityMedium-High. Issues with CDC.MediumHigh
Data Source AuthenticationOAuth / HTTPS / SSH / SSL / API TokensOAuth / HTTPS / SSH / SSL / API KeysOAuth 2.0 / API Tokens
HTTPS / SSH / SSL
EncryptionEncryption at rest, in-motionEncryption at rest, in-motionEncryption at rest, in-motion

Support and Cost Comparison: Fivetran vs Stitch vs Estuary Flow

Support and overall costs can significantly impact the long-term value of an ETL tool. This table highlights how Fivetran, Stitch, and Estuary Flow differ in terms of customer support, vendor costs, and associated engineering and administrative costs.

 FivetranStitchEstuary Flow
SupportMedium
Good G2 ratings but slow support has been a reason customers moved to Estuary.
Low-Medium
Open source support, and consulting
High
Fast support, engagement, time to resolution, including fixes.
 
Vendor costsHigh
Highest cost, much higher costs for non-relational data (SaaS apps)
Low-medium
Requires self-hosting open source
Low
2-5x lower than the others, becomes even lower with higher data volumes. Also lowers cost of destinations by doing in place writes efficiently and supporting scheduling
Data engineering costsLow-Med
Simplified dbt 
Good schema inference, evolution automation 
Med-High
Requires dbt
No automated schema evolution
Low-Med
2-4x greater
productivity, 
dbt or derivations
Good schema inference, evolution automation
Admin costsMed-High
Some admin and troubleshooting, CDC issues,
frequent upgrades
Med-High (self-managed open source)Low
“It just works”

Conclusion

If you’re looking at Fivetran vs Stitch, your choice should be relatively clear. Stitch can be a reasonable open source choice if all you need is batch-based ELT. Fivetran has more connectors, greater scale and reliability, but at a higher cost. If you need lower latency or even real-time data ELT or ETL, greater scale, and are looking for a lower cost option, Estuary Flow may be the best choice for you.


Get Started with Estuary Flow Today!

Join today and explore the future of real-time data integration. Get started here to elevate your data workflows with ease and efficiency!

To chat more about ETL and how we’re solving other engineering problems at Estuary, come and join us on Slack!


Frequently Asked Questions: Fivetran vs Stitch

1. What is the main difference between Fivetran and Stitch?

Fivetran offers more connectors, and great scalability and reliability. Stitch is based on open source.

2. Is Stitch truly cost-effective?

Stitch’s pricing starts at $100 per month, but costs can rise quickly with data volume. It’s important to consider your data needs and budget before choosing Stitch.

3. What are the limitations of Fivetran?

Fivetran’s monthly active row (MAR) based pricing can lead to high, unpredictable costs. Also, Fivetran’s limited to batch-based ELT compared to more comprehensive platforms like Estuary Flow.


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Daniel Harrington

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