Estuary

Estuary VS Fivetran

Read this detailed 2026 comparison of Estuary vs Fivetran. Understand their key differences, core features, and pricing to choose the right platform for your data integration needs.

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Comparison between Estuary and Fivetran
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Introduction

Estuary and Fivetran both move data from your databases, SaaS apps, and streams into warehouses, lakes, and operational systems, but they take different approaches. Estuary is a right-time data platform that handles change data capture, streaming, and batch in one system, so you set the cadence per pipeline, from sub-second streaming to scheduled batch, and pay based on the volume of data moved. Fivetran is a batch-first ELT platform with a large catalog of fully managed connectors, priced on monthly active rows (MAR), with real-time delivery available mainly through its self-hosted HVR option.

That difference shapes how fresh your data is, how predictable your bill stays as volume grows, and how much your team has to manage day to day. This guide compares Estuary vs Fivetran across nearly 40 criteria, from connector coverage and latency to pricing, security, and transformation support, so you can see which platform fits your current stack and where you're heading next.

Comparison Matrix: Estuary vs Fivetran

Estuary logo
Estuary
Fivetran logo
Fivetran
Database replication (CDC)EstuaryLog-based CDC for supported databases, including PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, and others.FivetranCDC for supported databases, with scheduled syncs as frequent as 1 minute on eligible Enterprise and Business Critical connectors. HVA supports real-time log-based replication for selected high-volume databases.
Operational integrationEstuary

Supports low-latency data delivery to operational databases, APIs, streaming systems, and other destinations.

Fivetran

Supports reverse ETL and data activation through Fivetran Activations, with 200+ managed activation destinations.

Data migrationEstuary

Supports historical backfills followed by continuous replication, with schema discovery and evolution for supported connectors.

Fivetran

Supports database replication, historical syncs, and automatic schema handling for supported sources and destinations.

Stream processingEstuary

Real-time transformations using SQL, TypeScript, or Python over durable collections.

Fivetran

Not a general-purpose stream-processing engine. HVA provides real-time database replication for selected sources.

Operational analyticsEstuary

Supports sub-second streaming pipelines as well as scheduled delivery for analytics and operational workloads.

Fivetran

Supports incremental replication and CDC, with sync frequencies down to 1 minute for eligible connectors and real-time replication through HVA for selected databases.

AI pipelinesEstuary

Supports real-time and batch data delivery to AI and vector-database destinations, with SQL, TypeScript, and Python transformations for data preparation.

Fivetran

Supports data movement and transformation for analytics and AI workloads. Fivetran and dbt Labs completed their merger in June 2026.

Apache Iceberg SupportEstuary

Supports streaming and batch materialization to Apache Iceberg through REST catalogs, including AWS Glue and other compatible catalogs.

Fivetran

Supports managed data lake destinations using Apache Iceberg, including catalog integrations such as AWS Glue, Databricks Unity Catalog, and Apache Polaris.

Industry specificEstuary

Estuary enables right-time data pipelines for operational workloads, real-time analytics, batch processing, and AI applications across any industry. Its low-latency CDC and streaming capabilities ensure fresh, dependable data movement at scale.

Fivetran

Fivetran provides reliable batch ELT for teams prioritizing cloud warehouse reporting and predictable scheduled syncs. Best suited for analytics use cases where minute-level latency is acceptable.

Number of connectorsEstuary200+ fully managed connectors across databases, SaaS applications, warehouses, lakes, files, and streaming systems.Fivetran700+ fully managed connectors, including standard and Lite connectors. Lite connectors are typically built for narrower API use cases and may cover fewer endpoints.
Streaming connectorsEstuarySupports CDC sources, Kafka, Kinesis, Google Pub/Sub, and Kafka-compatible consumption through Dekaf.FivetranHVA supports real-time CDC for selected databases. Standard connectors use scheduled syncs rather than continuous stream processing.
3rd party connectorsEstuary

Supports selected open-source connectors and the Airbyte source connector specification.

Fivetran
Custom SDKEstuary

Supports development of custom source and destination connectors using its open connector architecture.

Fivetran

Connector SDK and Partner SDK are available for building custom integrations. Fivetran also develops Lite connectors through its By Request program.

Request a connectorEstuary

Connector and connector-feature requests are accepted by the Estuary team.

Fivetran

Wait time on new feature requests can be long, even with a lot of community interest.

Batch and streamingEstuarySupports continuous streaming and scheduled batch delivery within the same platform.FivetranPrimarily scheduled ELT, with real-time log-based replication available through HVA for selected database sources.
Delivery guaranteeEstuaryTransactional processing with exactly-once semantics where the destination supports transactional or idempotent writes.FivetranExactly once (batch only)
ELT transformsEstuary

dbt Cloud integration and materialization triggers for downstream dbt workflows.

Fivetran

Primarily ELT; transformations generally run in the destination after data is loaded.

ETL transformsEstuary

In-flight transformations using SQL, TypeScript, and Python.

Fivetran

Hosted dbt Core transformations, dbt Cloud orchestration, Coalesce orchestration, and pre-built Fivetran data models.

Load write methodEstuaryAppend only or update in place (soft or hard deletes)FivetranAppend only or update in place (soft deletes; hard deletes with HVR)
DataOps supportEstuary

Web UI, CLI, APIs, declarative specifications, version control, and CI/CD workflows.

Fivetran

REST API, Terraform provider, monitoring and logging, scheduling, schema management, and transformation orchestration.

Schema inference and driftEstuary

Automatic schema discovery and schema evolution, with options for manual control.

Fivetran

Automatic schema detection and schema evolution for supported connectors.

Store and replayEstuary

Can backfill multiple targets and times without requiring new extract.

User-supplied cheap, scalable object storage.

Fivetran

Requires re-extraction of sources for new destinations

Time travelEstuary

Can restrict the data materialization process to a specific date range.

Fivetran

Row filtering (beta). Only supported for ~20 connector options. Cannot be used with incremental syncs.

SnapshotsEstuary

Full or incremental

Fivetran

N/A

Ease of useEstuary

No-code connector configuration through the web UI, with CLI and code-based options for advanced workflows.

Fivetran

Fully managed SaaS with automated connector maintenance and schema handling. HVA and Hybrid Deployment require additional customer-side setup.

Deployment optionsEstuaryPublic Deployment, Private Deployment, and Bring Your Own Cloud (BYOC).FivetranCloud, hybrid, self-hosted HVR
SupportEstuary

Slack and email support on Cloud; dedicated Slack and email support available with Enterprise.

Fivetran

Support portal and managed support options, with additional enterprise support features depending on plan.

Performance (minimum latency)Estuary< 100 ms (in streaming mode) Supports any batch interval as well and can mix streaming and batch in 1 pipeline.Fivetran15-minute syncs on Standard; 1-minute syncs on Enterprise and Business Critical for eligible standard connectors. HVA provides real-time replication for selected databases.
ReliabilityEstuaryTransactional processing, durable collections, recovery logs, and exactly-once semantics where supported by the destination.FivetranManaged connectors include automated retries, schema handling, and monitoring. Operational experience can vary by connector and source system.
ScalabilityEstuaryElastic processing for high-volume streaming and batch workloads.FivetranManaged scaling for standard connectors, with HVA designed for high-volume database replication.
SOC2Estuary

SOC 2 Type II with no exceptions

Fivetran
Data source authenticationEstuaryOAuth 2.0 / API Tokens SSH/SSLFivetranOAuth / HTTPS / SSH / SSL / API Tokens
EncryptionEstuaryEncryption at rest, in-motionFivetranEncryption at rest, in-motion
HIPAA complianceEstuary

HIPAA compliant; PHI workloads require a BAA and Private or BYOC deployment.

Fivetran

HIPAA BAA compliant

Vendor costsEstuary

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.

Fivetran

Usage-based pricing primarily based on Monthly Active Rows (MAR), with separate usage metrics for Activations and transformation model runs.

Data engineering costsEstuary

Managed connectors and infrastructure reduce pipeline operations, while custom connectors and advanced transformations can require engineering work

Fivetran

Fully managed connectors reduce connector maintenance, while custom transformations, HVA, and Hybrid Deployment can require additional engineering work.

Admin costsEstuary

Public Deployment is fully managed; Private and BYOC deployments require additional customer-side configuration and governance.

Fivetran

Generally low for managed SaaS pipelines; HVA and Hybrid Deployment require additional infrastructure configuration and administration.

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Estuary

Estuary

Estuary is a managed data integration platform for CDC, streaming, and batch pipelines. It supports database CDC, SaaS and API ingestion, event streams, files, warehouses, data lakes, operational systems, and AI destinations, with delivery ranging from real-time streaming to scheduled batch intervals.

At the center of Estuary is its runtime, where captured data is written to durable collections and can be independently read by multiple destinations and transformations. This separates source capture from downstream delivery and allows data to be reused for additional destinations, backfills, and reprocessing without repeatedly extracting it from the source.

Estuary offers 200+ fully managed connectors, no-code capture and materialization setup through the web application, and streaming transformations using SQL, Python, and TypeScript. It also supports dbt Cloud, materialization triggers, Agent Skills for AI-assisted pipeline development, and Public, Private, and Bring Your Own Cloud (BYOC) deployment options.

Pros

  • CDC, streaming, and batch in one platform: Estuary supports log-based CDC, SaaS and API ingestion, event streams, files, and scheduled batch movement for analytical and operational use cases.
  • Real-time runtime with durable collections: Estuary's runtime separates captures from materializations through durable collections, allowing data to be reused for multiple destinations, transformations, backfills, and replay without re-extracting it from the source.
  • Low-latency delivery: Supported real-time pipelines can deliver data with sub-second latency, while delivery can also be scheduled when lower freshness is sufficient.
  • No-code setup with advanced transformation options: Pipelines can be configured through the web application, while SQL, Python, and TypeScript transformations, dbt Cloud, APIs, and flowctl support more advanced workflows.
  • Built-in monitoring and AI-assisted operations: Estuary includes logs, latency and usage metrics, pipeline alerts, OpenMetrics integrations, and Agent Skills for AI-assisted pipeline development and troubleshooting.
  • Flexible deployment and predictable pricing: Public, Private, and BYOC deployments provide different levels of infrastructure control, while pricing is based on data volume and prorated connector task hours rather than Monthly Active Rows.

Cons

  • Smaller managed connector catalog than some large ELT platforms: Estuary offers 200+ fully managed connectors, but some larger platforms have broader packaged coverage, particularly for long-tail SaaS and legacy enterprise applications. Custom connector development is available with Enterprise.
  • No visual transformation canvas: Pipeline setup is no-code, and fields can be selected or renamed in the UI, but more complex streaming transformations use SQL, Python, or TypeScript rather than a drag-and-drop transformation canvas.
  • Advanced workflows have a learning curve: Basic capture and materialization pipelines can be built through the web application, but advanced derivations, schemas, CLI workflows, and GitOps-style deployments require more data engineering familiarity. Some Estuary users on G2 also mention a learning curve for more advanced configurations.

Estuary Pricing

Estuary pricing is based on data volume moved and connector instance usage. Data movement is priced at $0.50 per GB. The first six connector instances are priced at $100 per month each, while additional connector instances are $50 per month each, with usage prorated based on active connector instances.

The permanent free tier includes up to 10 GB of data movement per month and two concurrent connector instances, while the 30-day trial provides access to the full Cloud plan.

Enterprise plans can include volume discounts, Private or BYOC deployments, custom SLAs, private networking, dedicated support, and custom connector development.

Because pricing is based on GB moved plus connector usage rather than row-change metrics such as MAR, costs are relatively predictable from data volume and connector usage.

Fivetran

Fivetran introductory image

Fivetran is a managed data movement platform founded in 2012. It focuses on automating data ingestion from databases, SaaS applications, files, and other sources into cloud warehouses, databases, and data lakes. In June 2026, Fivetran completed its merger with dbt Labs, bringing its data movement platform together with dbt's data transformation ecosystem.

Fivetran offers 700+ fully managed connectors, including standard and Lite connectors. Lite connectors are generally designed for narrower API-based use cases and may support fewer endpoints, but generally available Lite connectors are maintained and supported by Fivetran. For high-volume database replication, Fivetran also offers High-Volume Agent (HVA) connectors with log-based CDC for selected databases.

Pros

  • Broad managed connector catalog: Fivetran offers 700+ fully managed connectors across SaaS applications, databases, files, warehouses, and other systems.
  • Low operational overhead: Managed connectors automate extraction, retries, schema handling, and connector maintenance, reducing the amount of pipeline infrastructure teams need to operate themselves.
  • Strong transformation ecosystem: Fivetran supports hosted dbt Core transformations, dbt Cloud and Coalesce orchestration, and pre-built data models. Fivetran and dbt Labs are now one company.
  • CDC for database sources: Fivetran supports log-based CDC for supported databases, with HVA available for selected high-volume and lower-latency replication workloads.
  • Flexible enterprise deployment: Hybrid Deployment allows data processing to remain inside the customer's environment while Fivetran manages orchestration through its cloud control plane.
  • Data activation: Fivetran Activations, built from its acquisition of Census, supports reverse ETL from warehouses and lakes into business applications.

Cons

  • MAR pricing can be difficult to predict: Fivetran primarily charges for data ingestion using Monthly Active Rows (MAR). Each connection contributes separately to MAR, and qualifying connections with 1 to 1 million MAR also have a monthly base charge. Recent Fivetran users on G2 have also cited unpredictable or rapidly increasing MAR costs for frequently updated datasets.
  • Lowest sync frequencies are limited by plan and connector: Fivetran Standard supports 15-minute syncs, while 1-minute syncs require Enterprise or Business Critical and are not supported by every standard connector or any Lite connector.
  • Real-time CDC has narrower coverage: Fivetran's High-Volume Agent (HVA) provides real-time log-based replication for selected high-volume database sources, rather than across its entire connector catalog.
  • Hybrid deployments require customer-side infrastructure: Fivetran Hybrid Deployment runs data processing inside the customer's environment, but requires a Hybrid Deployment Agent on customer-managed Kubernetes, Docker, or Podman infrastructure.
  • Support experience can vary: Fivetran provides managed support, but some recent G2 reviewers report difficulty reaching support or resolving issues beyond documentation-based troubleshooting.

Fivetran Pricing

Fivetran uses usage-based pricing. Data ingestion is primarily measured using Monthly Active Rows (MAR), which count distinct primary keys inserted, updated, or deleted and synced during a calendar month.

Fivetran offers Free, Standard, Enterprise, and Business Critical plans. The Free plan includes up to 500,000 connector MAR per month, while Standard includes 15-minute syncs and the managed connector catalog. Enterprise adds capabilities such as 1-minute syncs for eligible connectors, HVA, and additional governance features, while Business Critical adds advanced security and compliance capabilities.

Fivetran changed parts of its pricing model in 2025 and 2026. MAR volume tiering is now calculated at the connection level rather than across the entire account, and standard connections generating between 1 and 1 million MAR can have a minimum monthly connection charge. As a result, total cost depends not only on overall data volume but also on the number of connections and how frequently records change.

For those looking for Fivetran alternatives, it's worth considering solutions that offer lower costs, real-time streaming, or more flexibility in schema control.

How to choose the best option

The right data integration platform depends on which trade-offs match your needs. A few key questions worth answering:

  • Latency: Real-time streaming, batch, or both? Streaming-first and batch-first vendors are built around different architectures and pricing.
  • Connectivity: Modern ELT vendors cover cloud and SaaS well. Traditional ETL vendors handle legacy on-prem systems like mainframe and SAP ECC better. Pick based on where your sources actually live.
  • Cost model: Per-GB or per-hour pricing forecasts easily. MAR-based and row-based pricing can swing significantly. Run any model against your real volumes before signing.
  • CDC and schema evolution: Check latency guarantees, source coverage, and how schema drift is handled. ELT-only vendors typically support batch CDC, not streaming.
  • Vendor stability: Confluent is now part of IBM, Informatica is part of Salesforce, Talend is part of Qlik, and Rivery is now Boomi Data Integration. Acquisitions affect long-term pricing and roadmap.

Score the shortlisted vendors against the two or three dimensions that matter most for your situation, and weigh both current needs and where you expect to be in two to three years.

For teams prioritizing real-time streaming, predictable usage-based pricing, or AI-native workflows, Estuary is purpose-built around those needs.

Getting started with Estuary

  • Free account

    Getting started with Estuary is simple. Sign up for a free account.

    Sign up
  • Docs

    Make sure you read through the documentation, especially the get started section.

    Learn more
  • Community

    Join the Slack community for the easiest way to get support while getting started.

    Join Slack Community
  • Estuary 101

    Watch the Estuary 101 webinar for a guided introduction to using Estuary.

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