kafka-connect-bigquery
debezium
| kafka-connect-bigquery | debezium | |
|---|---|---|
| 2 | 80 | |
| 76 | 9,884 | |
| - | 1.1% | |
| 8.6 | 9.9 | |
| 4 days ago | 3 days ago | |
| Java | Java | |
| Apache License 2.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kafka-connect-bigquery
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Evolutionary Data Infrastructure
But is there a way to solve the schema problem? The answer is, yes, through KCBQ.
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Logical replication and decoding for Cloud SQL for PostgreSQL
Why the Parquet step? You should be able to do straight Debezium -> Kafka -> BQ, using the BQ sink connector for Kafka Connect (https://github.com/confluentinc/kafka-connect-bigquery); we have users using this with the Debezium MySQL connector, I'd expect this to work equally for Postgres.
Disclaimer: working on Debezium
debezium
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
They manage data in the application layer and your original data stays where it is. This way data consistency is no longer an issue as it was with streaming databases. You can use Change Data Capture (CDC) services like Debezium by directly connecting to your primary database, doing computational work, and saving the result back or sending real-time data to output streams.
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Generating Avro Schemas from Go types
Both of these articles mention a key player, Debezium. In fact, Debezium has had a place in the modern infrastructure. Let's use a diagram to understand why.
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debezium VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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How the heck do I validate records with this kind of data??
This might be overkill, but you could use an extra tool like https://debezium.io to capture logs about all creates, updates, and deletes in your table
- All the ways to capture changes in Postgres
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Managed Relational Databases with AWS RDS and Aurora
If you're considering a relational database for an event-driven architecture, check out Debezium. It lets you stream changes to relational databases, and subscribe to change events.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
Debezium
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Postgresql to hadoop in real time
https://debezium.io/ comes to mind as an open source product, but there are a gazillion of these tools out there.
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ClickHouse Advanced Tutorial: Apply CDC from MySQL to ClickHouse
Contrary to what it sounds, it’s quite straightforward. The database changes are captured via Debezium and published as events on Apache Kafka. ClickHouse consumes those changes in partial order by Kafka Engine. Real-time and eventually consistent.
- Debezium: Stream Changes from Your Database
What are some alternatives?
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
maxwell - Maxwell's daemon, a mysql-to-json kafka producer
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
hudi - Upserts, Deletes And Incremental Processing on Big Data.
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.
iceberg - Apache Iceberg
PostgreSQL - Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Embulk - Embulk: Pluggable Bulk Data Loader.
wal2json - JSON output plugin for changeset extraction
pgaudit - PostgreSQL Audit Extension