Estuary

ESTUARY FLOW

Estuary Flow is the only platform purpose-built for real-time ETL and ELT data pipelines. Batch-load for analytics, and stream for ops and AI - all set up in minutes, with millisecond latency.

Real-time ETL with Estuary Flow: Seamlessly move data from source to destination for immediate analysis and actionable insights.
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HOW IT WORKS

Oracle logo
Oracle
MySQL logo
MySQL
Postgre SQL logo
Postgre SQL

Streaming CDC

Amazon S3 logo
Amazon S3
Google Cloud Storage logo
GCS
Azure Blob Storage logo
ABS

Batch

Netsuite logo
Netsuite
Hubspot logo
HubSpot
Salesforce logo
Salesforce

SaaS

Google Cloud Pub Sub logo
Google PubSub
AWS Kinesis logo
Amazon Kinesis
Apache Kafka logo
Apache Kafka

Real-time

Analytics

Snowflake logo
Snowflake
Google BigQuery logo
Google Bigquery
Redshift logo
Amazon Redshift

Ops

ElasticSearch logo
Elastic
MongoDB logo
MongoDB
Amazon DynamoDB logo
Amazon DynamoDB

AI

Pinecone logo
Pinecone
Open AI logo
Open AI
Databricks logo
Databricks
Flow
Flow

Flow

Estuary Flow is built from the ground up for real-time ETL across databases, data warehouses, SaaS apps, and more. Just capture from sources, then materialize to destinations - all in minutes without coding. Let Estuary do the rest and manage the data pipeline all for you.

Oracle logo
Oracle
MySQL logo
MySQL
Postgre SQL logo
Postgre SQL

Streaming CDC

Amazon S3 logo
Amazon S3
Google Cloud Storage logo
GCS
Azure Blob Storage logo
ABS

Batch

Netsuite logo
Netsuite
Hubspot logo
HubSpot
Salesforce logo
Salesforce

SaaS

Google Cloud Pub Sub logo
Google PubSub
AWS Kinesis logo
Amazon Kinesis
Apache Kafka logo
Apache Kafka

Real-time

Capture
Capture
Capture

Capture

Capture change data in real-time from databases using streaming CDC, real-time messaging, APIs, SaaS apps and more.

Stream, Store, Transform, Replay
Stream, Store, Transform, Replay
Stream, Store, Transform, Replay

Stream, Store, Transform, Replay

Stream data exactly with sub-100ms latency to all destinations, transform it as needed. Store data reliably as it streams using collections, durable transaction logs of unlimited size, and replay collections to backfill data or time travel.

Materialize

Analytics

Snowflake logo
Snowflake
Google BigQuery logo
Google Bigquery
Redshift logo
Amazon Redshift

Ops

ElasticSearch logo
Elastic
MongoDB logo
MongoDB
Amazon DynamoDB logo
Amazon DynamoDB

AI

Pinecone logo
Pinecone
Open AI logo
Open AI
Databricks logo
Databricks
Materialize
Materialize

Materialize

Write data at any speed, from real-time streaming to hour+ intervals, into side-by-side destinations to support analytics, operations, and AI. Update data in place or add all change data as needed.

    KEY FEATURES

    Estuary Flow stands out because it brings together the best of CDC, real-time, and batch with modern data engineering best practices, enabling the best of both worlds, without managing infrastructure.

    Connect apps, analytics, and AI using 100s of streaming CDC, real-time, and batch no-code connectors built by Estuary for speed and scale.

    Perform end-to-end streaming CDC.

    • Stream transaction logs + incremental backfill.
    • Capture change data to a collection.
    • Reuse for transformations or destinations.

    Use Flow Dekaf to connect any Kafka-compatible destination to Flow as if it were a Kafka cluster via the destination's existing Kafka consumer API support.

    Connect apps, analytics, and AI using 100s of streaming CDC, real-time, and batch no-code connectors built by Estuary for speed and scale.

    As you capture data, Flow automatically stores each stream as a reusable collection, like a Kafka topic but with unlimited storage. It is a durable append-only transaction log stored in your own private account so you can set security rules and encryption.

    Flow

    Transform and derive data in real-time (ETL), using SQL or Typescript for operations, or use dbt to transform data (ELT) for analytics.

    Move data from many sources to collections, then to many destinations all at once. Share and reuse data across projects, or replace sources and destinations without impacting others.

    Reuse collections to backfill destinations enabling fast and effective one-to-many distribution, streaming transformations and time travel, at any time.

    Automatically inferred and managed from source to destination using schema evolution.

    • Automated downstream updates.
    • Continuous data validation and testing.

    CLI and API Automation using flowctl.

    Deploy each capture, SQL or TypeScript task, and materialization of a single pipeline in the same or different public or private clouds and regions.

    CREATE A DATA PIPELINE IN MINUTES

    Build new data pipelines that connect many sources to many destinations in minutes.

    Create a data pipeline - Step 1

    1

    Add 100s of sources and destinations using no-code connectors for streaming CDC, real-time, batch, and SaaS. (see connectors).

    Create a data pipeline - Step 2

    2

    Choose any speed for each connection from real-time to hour+ batch; schedule fast updates when you need them to save money.

    Create a data pipeline - Step 3

    3

    Write in-place updates or the full change history into a destination.

    Analytics - pie chart
    Ops
    AI - artificial intelligence

    THE SAME DATA ACROSS ANALYTICS, OPS, AND AI

    Add data from your sources into collections. Then reuse that data for any destinations in real-time or batch.

    Analytics
    Ops
    AI
    Estuary logo
    Flow path with arrow
    Analytics Connectors

    Load into BigQuery, Databricks, Redshift or Snowflake for analytics.

    Coding optional

    CONFIGURE OR CODE

    Choose the best combination of no-code configuration and coding to move and transform data.

    • Use 100s of no-code connectors for apps, DBs, DWs, and more.

    • Use the Flow UI to build without coding, or the flowctl CLI for development.

    • Transform using Streaming SQL (ETL) and Typescript (ETL) or dbt (ELT) in your warehouse.

    Coding optional
    Boost Efficiency with flowctl: Automate DataOps, Integrate Tooling, and Streamline Schema Evolution

    USE MODERN DATAOPS

    Rely on built-in data pipeline best practices, integrate tooling, and automate DataOps to improve productivity and reduce downtime.

    • Automate DataOps and integrate with other tooling using the flowctl CLI.

    • Use built-in pipeline testing to validate data and pipeline flows automatically.

    • Select advanced schema detection and automate schema evolution.

    Schema evolution options
    Maximize efficiency, reduce expenses

    INCREASE PRODUCTIVITY, LOWER COSTS

    • Be 4x more productive and focus more new development, less on troubleshooting.

    • Spend 2-5x less with low, predictable pricing (see pricing.)

    • Minimize source loads and costs by extracting data only once from each source.

    • Lower destination costs by using real-time extraction with batch loading. Then schedule faster updates only when you need them.

    Case study - Connect & Go logo

    CONNECT&GO

    Connect&GO lowers MySQL to Snowflake latency up to 180x, improves productivity 4x with Estuary.

    Case study - True logo

    TRUE PLATFORM

    True Platform reduced its data pipeline spend by >2x and discovered seamless, scalable data movement.

    Case study - Soli & Company logo

    SOLI & COMPANY

    Soli & Company trusts Estuary's approachable pricing and quick setup to deliver change data capture solutions.

    Real-time data

    DELIVER REAL-TIME DATA AT SCALE

    Estuary Flow delivers reliable, real-time performance in production for over 3,000 active users, including some the most demanding workloads proven to 10x the scale of the alternatives.

    • Stream in real-time at any scale, running over 7GB/sec in production just for 1 customer.

    • Ensure data is never lost with exactly-once transactionally storage and delivery.

    • Use built-in monitoring and alerting, and active-active load balancing and failover.

    Estuary performance metrics
    Estuary logo

    7+GB/sec

    Single dataflow

    3000+

    Active users

    <100ms

    Latency

    Secure Your Data with Estuary Flow: GDPR, CCPA, CPRA Compliant & SOC 2 Type II Certified

    SECURE YOUR DATA

    Estuary Flow is designed and tested to make sure your data and your systems stay secure.

    • Estuary never stores your data.

    • GDPR, CCPA and CPRA compliant.

    • SOC 2 Type II certified.

    Secure Your Data with Estuary Flow: Compliance and Certification

    STREAMING ETL VS. BATCH ELT

    Key feature - Real-time and batch

    STREAMING ETL

    With Estuary, you extract data exactly and only once using CDC, real-time, or batch; use ELT and ETL; and deliver to many destinations with one pipeline.

    Key feature - Real-time and batch

    BATCH

    SaaS ELT tools are batch only, point-to-point replication. Each destination requires its own pipeline and source extractions, adding loads, costs, and time.

    HOW ESTUARY FLOW COMPARES

    Feature Comparison

    EstuaryBatch ELT/ETLDIY PythonKAFKA
    Price$$$-$$$$$-$$$$$-$$$$
    Speed<100ms5min+Varies<100ms
    EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
    Scale
    View Comparisons
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