Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Databricks
Qubole
Snowflake
HortonWorks Data Platform
Airbyte
Fivetran
Meltano
QuickBI
Supermetrics
Segment
Zapier
Hevo Data
Amazon EMR AirbyteBased on our record, Airbyte should be more popular than Amazon EMR. It has been mentiond 45 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
AgentCloud uses Airbyte to build data pipelines, which allow us to split, chunk, and embed data from over 300 data sources, including Postgres. - Source: dev.to / 3 days ago
I'l also give a shout-out to Airbyte (https://airbyte.com/), with which I've had some limited success with integrating Salesforce to a local database. The particular pull for Airbyte is that we can self-host the open source version, rather than pay Fivetran a significant sum to do this for us. It's an immature tool, so I don't yet know that I can claim we've spent _less_ than... - Source: Hacker News / 5 months ago
As possible solution, I can suggest Airbyte(https://airbyte.com/). it's more performant than generic python script. Source: 10 months ago
Airbyte, an open-source data integration engine that offers hundreds of connectors with data warehouses and databases, has gained popularity for its seamless integration and data syncing capabilities. Xata's integration with Airbyte offers a streamlined data ingestion process from any Airbyte input source directly into your Xata database. - Source: dev.to / 10 months ago
In conclusion, data integration is not just a luxury for companies but a necessity for striving toward success in today’s data-driven world. In today’s competitive business environment, those who can effectively integrate and leverage data from different sources will have a strategic advantage over others who don’t. So, as technology continues to advance and data continues to grow exponentially, businesses that... - Source: dev.to / about 1 year ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Fivetran - Fivetran offers companies a data connector for extracting data from many different cloud and database sources.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Meltano - Open source data dashboarding
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
QuickBI - Export data from over 300 sources to a data warehouse and analyze it with a reporting tool of your choice. Quick and easy setup.