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What is Airbyte?

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.
Airbyte is a tool in the Big Data as a Service category of a tech stack.
Airbyte is an open source tool with 11.7K GitHub stars and 3K GitHub forks. Here’s a link to Airbyte's open source repository on GitHub

Who uses Airbyte?

20 companies reportedly use Airbyte in their tech stacks, including Labs, Ornikar, and Seenons B.V..

46 developers on StackShare have stated that they use Airbyte.

Airbyte Integrations

GitHub, MySQL, Slack, Google Analytics, and PostgreSQL are some of the popular tools that integrate with Airbyte. Here's a list of all 39 tools that integrate with Airbyte.
Pros of Airbyte
Easy to use
Change Data Capture
Connect Multiple Sources
Multiple capabilities
Decisions about Airbyte

Here are some stack decisions, common use cases and reviews by companies and developers who chose Airbyte in their tech stack.

Cyril Duchon-Doris

Hello, For security and strategic reasons, we are migrating our apps from AWS/Google to a cloud provider with more security certifications and fewer functionalities, named Outscale. So far we have been using Google BigQuery as our data warehouse with ELT workflows (using Stitch and dbt ) and we need to migrate our data ecosystem to this new cloud provider.

We are setting up a Kubernetes cluster in our new cloud provider for our apps. Regarding the data warehouse, it's not clear if there are advantages/inconvenients about setting it up on kubernetes (apart from having to create node groups and tolerations with more ram/cpu). Also, we are not sure what's the best Open source or on-premise tool to use. The main requirement is that data must remain in the secure cluster, and no external entity (especially US) can have access to it. We have a dev cluster/environment and a production cluster/environment on this cloud.

Regarding the actual DWH usage - Today we have ~1.5TB in BigQuery in production. We're going to run our initial rests with ~50-100GB of data for our test cluster - Most of our data comes from other databases, so in most cases, we already have replicated sources somewhere, and there are only a handful of collections whose source is directly in the DWH (such as snapshots, some external data we've fetched at some point, google analytics, etc) and needs appropriate level of replication - We are a team of 30-ish people, we do not have critical needs regarding analytics speed, and we do not need real time. We rebuild our DBT models 2-3 times a day and this usually proves enough

Apart from postgreSQL, I haven't really found open-source or on-premise alternatives for setting up a data warehouse, and running transformations with DBT. There is also the question of data ingestion, I've selected Airbyte and @meltano and I have troubles understanding if one of the 2 is better but Airbytes seems to have a bigger community.

What do you suggest regarding the data warehouse, and the ELT workflows ? - Kubernetes or not kubernetes ? - Postgresql or something else ? if postgre, what are the important configs you'd have in mind ? - Airbyte/DBT or something else.

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Airbyte's Features

  • 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

Airbyte Alternatives & Comparisons

What are some alternatives to Airbyte?
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
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.
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.
Amazon EMR
It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
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.
See all alternatives

Airbyte's Followers
88 developers follow Airbyte to keep up with related blogs and decisions.