temporal_tables
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temporal_tables | debezium | |
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16 | 80 | |
897 | 9,857 | |
- | 2.0% | |
4.2 | 9.9 | |
2 months ago | 6 days ago | |
C | Java | |
BSD 2-clause "Simplified" License | Apache License 2.0 |
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temporal_tables
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All the ways to capture changes in Postgres
There is also the temporal_tables extension.
[0] https://github.com/arkhipov/temporal_tables
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Show HN: I made a CMS that uses Git to store your data
- https://github.com/arkhipov/temporal_tables
I haven't used any of these but I work on https://xtdb.com which is also implementing SQL:2011's temporal features :)
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Data point versioning infrastructure for time traveling to a precise point in time?
It seems like PG has this extension here anyone ever use it?
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Questions about history table pattern
You could look at that or ask me questions about it (disclaimer, I am the author). Also there is https://github.com/arkhipov/temporal_tables/
- Modern solutions for database auditing?
- How Postgres Audit Tables Saved Us from Taking Down Production
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spring-data-jpa-temporal: a lightweight temporal auditing library
All good. Note there is also https://github.com/arkhipov/temporal_tables/ (which is also type 4 as a postgres extension - pretty similar to what ebean orm is doing)
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Time-travel options for databases
The Temporal Tables Postgres extension works well. https://github.com/arkhipov/temporal_tables
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easy master<->master postgresql 11 cluster solution?
If you're doing this across regions, you really really should reconsider. If you're doing it in the same data center you might be able to get away with it (but then I'm not sure why you're doing it in the first place, if the system fits in one DC then you probably can just scale up). It might be worth considering a sharded & passively combined approach -- i.e. every country has it's own data, and there's some huge public schema which consists of all the data that is drip fed in to materialized views or tables at regular intervals. You could also combine this with temporal_tables to get a very delayed but theoretically time-consistent (well, aside from clock skew across regions of course...) view of your DB to query... Really depends on the use case.
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SQLite the only database you will ever need in most cases
One of postgres's most underrated features. RLS is amazing, can be unseen/basically work silently if your programming language-side tools are good enough, and is documented well (like everything else):
https://www.postgresql.org/docs/current/ddl-rowsecurity.html
But the power of PG is that it doesn't stop there, if you combine this with a plugin like temporal_tables and you can segment by user and time:
https://github.com/arkhipov/temporal_tables
All of this mostly unknown to the thing that's accessing the DB. If that's not enough for you, why not add some auditing with pgaudit:
https://www.pgaudit.org/#section_three
I think it might not actually be hyperbole to say that Postgres is the greatest RDBMS database that has ever existed.
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?
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
maxwell - Maxwell's daemon, a mysql-to-json kafka producer
pg_bitemporal - Bitemporal tables in Postgres
kafka-connect-bigquery - A Kafka Connect BigQuery sink connector
pgaudit - PostgreSQL Audit Extension
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
dolt - Dolt – Git for Data
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
datasette - An open source multi-tool for exploring and publishing data
hudi - Upserts, Deletes And Incremental Processing on Big Data.
beekeeper-studio - Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more. Linux, MacOS, and Windows.
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.