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Airbyte
ByAirbyteAirbyte

Airbyte

#99in Databases
Discussions1
Followers112
OverviewDiscussions1Adoption

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 Databases category of a tech stack.

Key Features

Scheduled updatesManual full refreshReal-time monitoringDebugging autonomyOptional normalized schemasFull control over the dataBenefit from the long tail of connectors, and adapt them to your needsBuild connectors in the language of your choice, as they run in Docker containers

Airbyte Pros & Cons

Pros of Airbyte

  • ✓Change Data Capture
  • ✓Connect Multiple Sources
  • ✓Easy to use
  • ✓Free
  • ✓Multiple capabilities

Cons of Airbyte

No cons listed yet.

Airbyte Alternatives & Comparisons

What are some alternatives to 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.

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.

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.

Stitch

Stitch

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.

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.

Try It

Visit Website

Adoption

On StackShare

Airbyte Integrations

Greenhouse, Google Cloud Platform, Mixpanel, Google Analytics, PostgreSQL and 7 more are some of the popular tools that integrate with Airbyte. Here's a list of all 12 tools that integrate with Airbyte.

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
Mailchimp
Mailchimp
GitHub
GitHub

Airbyte Discussions

Discover why developers choose Airbyte. Read real-world technical decisions and stack choices from the StackShare community.

Cyril Duchon-Doris
Cyril Duchon-Doris

CTO at My Job Glasses

Aug 24, 2022

Needs adviceonGoogle BigQueryGoogle BigQueryStitchStitchdbtdbt

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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