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TiDB - Distributed NewSQL database compatible with MySQL protocol
TiDB is a distributed SQL database. Inspired by the design of Google F1 and Google Spanner, TiDB supports the best features of both traditional RDBMS and NoSQL. It is horizontally scalable, grow TiDB as your business grows. You can increase the capacity simply by adding more machines.
rdbms distributed-rdbms distributed-database distributed-transactions newsql mysql-protocoltikv - Distributed transactional key value database powered by Rust and Raft
Geo-Replication TiKV uses Raft and Placement Driver to support Geo-Replication.Horizontal scalability With Placement Driver and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to 100+ TBs of data.
distributed-transactions raft key-value tikv consensus rocksdb tidbCAP - CAP is a library based on
CAP is a library based on .Net standard, which is a solution to deal with distributed transactions, also has the function of EventBus, it is lightweight, easy to use, and efficiently.In the process of building an SOA or MicroService system, we usually need to use the event to integrate each services. In the process, the simple use of message queue does not guarantee the reliability. CAP is adopted the local message table program integrated with the current database to solve the exception may occur in the process of the distributed system calling each other. It can ensure that the event messages are not lost in any case.
kafka rabbitmq eventbus dotnetcore distributed-transactions transaction microservicetikv - Distributed transactional key-value database, originally created to complement TiDB
TiKV is an open-source, distributed, and transactional key-value database. Unlike other traditional NoSQL systems, TiKV not only provides classical key-value APIs, but also transactional APIs with ACID compliance. Built in Rust and powered by Raft, TiKV was originally created to complement TiDB, a distributed HTAP database compatible with the MySQL protocol. The design of TiKV ('Ti' stands for titanium) is inspired by some great distributed systems from Google, such as BigTable, Spanner, and Percolator, and some of the latest achievements in academia in recent years, such as the Raft consensus algorithm.
distributed-transactions raft key-value tikv consensus rocksdb tidb cncftrace-nodejs - Trace is a visualised distributed tracing platform designed for microservices.
With version 3.x.x we have dropped support for Node v0.10. This means that future releases under this major version might contain code changes that are incompatible with Node.js v0.10 to an extent of crashing your application. Please consider updating to a newer runtime, especially that the maintenance of v0.10 has already ended. See our compatibility table below. Also, since 3.1.0 we switched to a different API backend for collecting traces which is incompatible with the old one. The old endpoint is still supported, but we would like it to be phased out eventually. Please update your agents to 3.1.0 or newer.
nodejs monitoring debugging microservices performance distributed-transactions profiling instrumentation stackinfluxcloud - This is a fork of influxdb and try to make the current influxdb into a cluster.
influx-meta is ready to go. But this need corporate with influxd. Comparing with current influxd, we have to append a cluster service. In this way, It enables the communication channel between data node and meta node.Well, you do not need worry this in a month. The prototype is still under implementing. But we promise, we will try hard to get things done quickly.
time-series influxdb-cluster raft-consensus-algorithm distributed-transactionsgo-saga - Implements saga-pattern in Go, another way to distribute transaction.
[](https://godoc.org/github.com/lysu/go-saga) [](https://travis-ci.org/lysu/go-saga)
saga saga-pattern transaction distributed-transactionsendurox - Enduro/X Middleware Platform for Distributed Transaction Processing
It is modern, microservices based middleware for writing distributed, open systems (program consists of several executables) based applications. Thus by using Enduro/X programmers do not have to worry about threads and concurrency anymore, the load balacing and multi-CPU loading is done by Enduro/X middleware by it self, administrator only have to determine how many copies of particular services should be started. Of-course Enduro/X supports multi-threaded applications too, but now system architects have a choice either to design multi-threaded executables or just configure number of executables to start. For local inter-process-communication (IPC) Enduro/X uses kernel memory based Posix queues to avoid overhead of the TCP/IP protocol which is used in other middlewares or REST based microservice architectures. Thus this approach greatly increases application speed, as kernel queues is basically a matter of block memory copy from one process to another (by contrast of 7 layers of TCP/IP stack and streaming nature of the sockets vs block copy).
ipc cluster multiprocessing atmi tuxedo enduro service-orchestration distributed-transactions oracle realtime realtime-message
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