distributed-transactions

I am trying to understand how three-phase commit avoids blocking Consider the following two failure scenarios: Scenario 1: In phase 2 the coordinator sends preCommit messages to all cohorts and has gotten an ack from all except cohort A. Network problems prevent cohort A from receiving the coordinator's preCommit message. Cohort A times out waiting for the preCommit message and chooses to abort. Then both the coordinator and cohort A crash. Scenario 2: The protocol reaches phase 3. The coordinator sends a doCommit message to cohort A. But before it can send more doCommit messages the

If you create an Oracle dblink you cannot directly access LOB columns in the target tables. For instance, you create a dblink with: create database link TEST_LINK connect to TARGETUSER IDENTIFIED BY password using 'DATABASESID'; After this you can do stuff like: select column_a, column_b from data_user.sample_table@TEST_LINK Except if the column is a LOB, then you get the error: ORA-22992: cannot use LOB locators selected from remote tables This is a documented restriction . The same page suggests you fetch the values into a local table, but that is... kind of messy: CREATE TABLE tmp_hello AS

There are NoSQL ACID (distributed) databases , despite CAP theorem. How this is possible? What's the relation between CAP theorem and (possible/not possible of) being ACID? Is impossible for a distributed computer system to simultaneously provide consistency, availability and partition tolerance. CAP theorem is actually a bit misleading. The fact you can have a CA design is nonsense because when a partition occurs you necessarily have a problem regarding consistency (data synchronization issue for example) or availability (latency). That's why there is a more accurate theorem stating that :

We have a micro-services architecture, with Kafka used as the communication mechanism between the services. Some of the services have their own databases. Say the user makes a call to Service A, which should result in a record (or set of records) being created in that service’s database. Additionally, this event should be reported to other services, as an item on a Kafka topic. What is the best way of ensuring that the database record(s) are only written if the Kafka topic is successfully updated (essentially creating a distributed transaction around the database update and the Kafka update)?

I have a Customer container with items representing a single customer in SQL API (DocumentDB) in CosmosDB . I also have a Gremlin API (GraphDB) with the customers' shoppingcart data. Both these data are temporary/transient. The customer can choose clear shopping cart which will delete the temporary customer and the shoppingcart data. Currently I make separate calls, one to the SQL API (DocumentDB) and Gremlin API (GraphDB) which works but I want to do both as a transaction (ACID principle). To delete a customer , I call the Gremblin API and delete the shoppingcart data, then call the SQL API

We are trying to use IBM MQ manager as XA Transaction manager with spring-jms and spring transaction support. Does IBM MQ manager play well with spring-jta support? whitfiea You can't use the WMQ JMS client (which is what spring-jms would use) with the MQ QueueManager acting as the XA transaction manager. The intention is that a JMS application would be controlled via a JTA implemented transaction manager (i.e. a Java EE application server). You can however use the WMQ Java client (i.e. non JMS) and have the MQ QueueManager act as the XA transaction manager (non JTA). As @COLINHY said you can