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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Airbyte vs Stitch

Airbyte vs Stitch

OverviewComparisonAlternatives

Overview

Stitch
Stitch
Stacks150
Followers150
Votes12
Airbyte
Airbyte
Stacks105
Followers112
Votes5
GitHub Stars20.0K
Forks4.9K

Airbyte vs Stitch: What are the differences?

Introduction

Airbyte and Stitch are both data integration platforms designed to help businesses streamline and automate the process of data extraction, transformation, and loading (ETL). While they share similarities in terms of functionality, there are several key differences between the two.

  1. Connectivity and Integration Options: One of the key differences between Airbyte and Stitch lies in their connectivity and integration options. Airbyte offers a wide range of connectors that allow users to connect and integrate data from various sources such as databases, cloud storage services, and APIs. In contrast, Stitch primarily focuses on integrating data from cloud-based sources, with a limited number of native connectors available for non-cloud sources.

  2. Open-Source vs. Managed Service: Another important distinction between Airbyte and Stitch is their deployment model. Airbyte is an open-source data integration platform that can be self-hosted, giving users more control and flexibility over their infrastructure. On the other hand, Stitch is a managed service provided by Talend, which means that it is hosted and maintained by the company, removing the need for users to manage the underlying infrastructure.

  3. Pricing Structure: Airbyte and Stitch differ in their pricing structures. Airbyte follows an open-source model, offering its core features for free. Users can either self-host the platform or opt for Airbyte Cloud, a managed service provided by the developers. Stitch, on the other hand, operates on a subscription-based pricing model, with different pricing tiers based on the volume of data processed.

  4. Transformation and Data Manipulation Capabilities: When it comes to transformation and data manipulation capabilities, Airbyte and Stitch have different approaches. Airbyte focuses on providing a robust and extensible framework that allows users to define and execute custom transformations using SQL and Python. Stitch, on the other hand, offers a simpler approach with limited built-in data transformation capabilities, relying more on users' destination platforms for data manipulation.

  5. Data Replication and Sync Frequencies: Airbyte and Stitch also differ in their data replication and sync frequencies. Airbyte provides near real-time data replication, allowing users to set up frequent sync intervals to ensure that their data is always up to date. Stitch, on the other hand, offers batch-oriented data replication, where data is synced at pre-defined intervals, typically ranging from a few minutes to several hours.

  6. Community and Support: Lastly, Airbyte and Stitch vary in terms of community and support. Airbyte has a growing community of developers and users who actively contribute to the project, providing feedback, bug fixes, and additional connectors. Stitch, being a managed service by Talend, offers professional support and extensive documentation but may have a more limited user community compared to Airbyte.

In summary, Airbyte and Stitch differ in terms of connectivity and integration options, deployment model, pricing structure, transformation capabilities, data replication frequencies, and community/support. These differences allow users to choose the platform that best suits their specific needs and preferences.

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Detailed Comparison

Stitch
Stitch
Airbyte
Airbyte

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

Connect to your ecosystem of data sources - UI allows you to configure your data pipeline in a way that balances data freshness with cost and production database load;Replication frequency - Choose full or incremental loads, and determine how often you want them to run - from every minute, to once every 24 hours; Data selection - Configure exactly what data gets replicated by selecting the tables, fields, collections, and endpoints you want in your warehouse;API - With the Stitch API, you're free to replicate data from any source. Its REST API supports JSON or Transit, and recognizes your schema based on the data you send.;Usage dashboard - Access our simple UI to check usage data like the number of rows synced by data source, and how you're pacing toward your monthly row limit;Email alerts - Receive immediate notifications when Stitch encounters issues like expired credentials, integration updates, or warehouse errors preventing loads;Warehouse views - By using the freshness data provided by Stitch, you can build a simple audit table to track replication frequency;Scalable - Highly Scalable Stitch handles all data volumes with no data caps, allowing you to grow without the possibility of an ETL failure;Transform nested JSON - Stitch provides automatic detection and normalization of nested document structures into relational schemas;Complete historical data - On your first sync, Stitch replicates all available historical data from your database and SaaS tools. No database dump necessary.
Scheduled updates; Manual full refresh; Real-time monitoring; Debugging autonomy; Optional normalized schemas; Full control over the data; Benefit from the long tail of connectors, and adapt them to your needs; Build connectors in the language of your choice, as they run in Docker containers
Statistics
GitHub Stars
-
GitHub Stars
20.0K
GitHub Forks
-
GitHub Forks
4.9K
Stacks
150
Stacks
105
Followers
150
Followers
112
Votes
12
Votes
5
Pros & Cons
Pros
  • 8
    3 minutes to set up
  • 4
    Super simple, great support
Pros
  • 1
    Connect Multiple Sources
  • 1
    Multiple capabilities
  • 1
    Easy to use
  • 1
    Change Data Capture
  • 1
    Free
Integrations
Stripe
Stripe
Twilio SendGrid
Twilio SendGrid
Zendesk
Zendesk
MongoDB
MongoDB
Marketo
Marketo
Recurly
Recurly
GitLab
GitLab
Zapier
Zapier
FreshDesk
FreshDesk
Harvest
Harvest
Greenhouse
Greenhouse
Google Cloud Platform
Google Cloud Platform
Mixpanel
Mixpanel
Google Analytics
Google Analytics
PostgreSQL
PostgreSQL
MySQL
MySQL
Shopify
Shopify
Amazon EC2
Amazon EC2
Zendesk
Zendesk
Stripe
Stripe

What are some alternatives to Stitch, Airbyte?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Cloudera Enterprise

Cloudera Enterprise

Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

Treasure Data

Treasure Data

Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.

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