sqlize
dtm
| sqlize | dtm | |
|---|---|---|
| - | 20 | |
| 80 | 5,149 | |
| - | - | |
| 4.3 | 9.8 | |
| about 2 months ago | about 2 years ago | |
| Go | Go | |
| GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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sqlize
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dtm
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How to reliably sync 2 application databases
- using a distributed transaction framework (like https://github.com/dtm-labs/dtm)
- Examples code for DTM Saga
- dtm 1.15.1 Released – A lightweight workflow engine to orchestrate micro-services for distributed transactions.
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Use workflow to handle distributed transactions
But in this article, we introduce a workflow pattern in github.com/dtm-labs/dtm. Under this pattern, a mixture of XA, SAGA and TCC can be applied to different branches in a single distributed transactions, allowing users to customize most of the contents of a distributed transaction, providing great flexibility.
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How to elegantly implement a multi-database outbox pattern
The open source distributed transaction framework https://github.com/dtm-labs/dtm has a two-stage message pattern inside that handles this problem very well. The following is an example of the use of an interbank transfer operation.
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How to Manage Anomalies in Saga Pattern in Microservices
The above Sub-transaction Barrier technique, when used in conjunction with the distributed transaction framework https://github.com/dtm-labs/dtm, has been made available in several language SDKs, with the following example code in Go.
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Building financial integration with Cadence in doordash
Maybe you can take a look at github.com/dtm-labs/dtm which provide built-in TCC pattern
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Understanding XA Transactions With Practical Examples in Go
Distributed XA transactions can solve the above business problem. This article presents a solution based on dtm-labs/dtm. DTM is a popular distributed transaction framework which supports XA, Saga, OutBox, and TCC patterns.
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dtm 1.13.5 Released – A distributed transaction framework that supports saga, tcc, xa, outbox patterns.
Github: https://github.com/dtm-labs/dtm
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How to Implement a Distributed Transaction Across Mysql, Redis, and Mongo
This article gives an example of implementing a distributed transaction across multiple store engines, Mysql, Redis and Mongo. This example is based on the Distributed Transaction Framework https://github.com/dtm-labs/dtm and will hopefully help to solve your problems in data consistency across microservices.
What are some alternatives?
Squirrel - Fluent SQL generation for golang
Seata - :fire: Seata is an easy-to-use, high-performance, open source distributed transaction solution.
prometheus - The Prometheus monitoring system and time series database.
go-cache - An in-memory key:value store/cache (similar to Memcached) library for Go, suitable for single-machine applications.
badger - Fast key-value DB in Go.
temporal - Temporal service
go-mysql-elasticsearch - Sync MySQL data into elasticsearch
bolt
dbr - Additions to Go's database/sql for super fast performance and convenience.
InfluxDB - Scalable datastore for metrics, events, and real-time analytics
chproxy - Open-Source ClickHouse http proxy and load balancer
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.