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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 16.5K GitHub stars and 4.2K GitHub forks. Here’s a link to Airbyte's open source repository on GitHub

Who uses Airbyte?

Companies
26 companies reportedly use Airbyte in their tech stacks, including technology, Yousign, and Labs.

Developers
64 developers on StackShare have stated that they use Airbyte.

Airbyte Integrations

GitHub, MySQL, Slack, PostgreSQL, and Google Analytics are some of the popular tools that integrate with Airbyte. Here's a list of all 42 tools that integrate with Airbyte.
Pros of Airbyte
1
Easy to use
1
Change Data Capture
1
Connect Multiple Sources
1
Free
1
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?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
See all alternatives

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