Spring Team
Christoph Strobl

Christoph Strobl

Spring Data Committer

Pregarten, Austria

Blog Posts by Christoph Strobl

Spring Data Moore M3 released

Hot on the heels of Spring Framework 5.2 M1 and just in time for the upcoming Spring Boot 2.2 M2 release, on behalf of the Spring Data team, I’m pleased to announce the availability of the third milestone of the Moore release train.

Notable changes amongst many others:

  • Flow extensions for Kotlin coroutines in Spring Data for Apache Cassandra & MongoDB.
  • MongoDB Json Schema generation from domain Types.
  • Support for BINARY storage type in Spring Data JDBC.
  • Alternative EntityMapper for Elasticsearch.
  • Improved Geospatial query support for Neo4j.
  • Smarter Redis cluster topology caching.
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Spring Data Moore M2 released

On behalf of the Spring Data team, I’m pleased to announce the availability of the second milestone of the Moore release train.

Notable changes include:

  • Support for Kotlin Coroutines in Spring Data MongoDB, Cassandra and Redis.
  • Querydsl support for reactive repositories.
  • Range type support for derived repository query methods using between for Spring Data MongoDB & Cassandra.
  • exists projection in Neo4j repositories.
  • Reactive repositories for Spring Data Elasticsearch.
  • Pivotal Gemfire and Apache Geode upgrades.
  • Upgrade to Spring HATEOAS 1.0 M1.
  • …and numerous features for the JDBC module like direct insert & update methods skipping the is new check.
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Spring Data Moore M1 released

On behalf of the Spring Data team, I’m pleased to announce the availability of the first milestone of the Moore release train.

Notable changes include:

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What's new in Spring Data Lovelace for MongoDB?

The past year has seen a lot of enhancements brought to the NoSQL Store including a bunch of new features and extended capabilities. We collaborated closely with the driver team at MongoDB, so the release already ships with decent support for sessions, change streams, schema validation, and (of course) transactions.

The most interesting new feature is probably MongoDB 4.0’s support for Multi-Document Transactions. If you have followed this blog before, you have probably read our Hands on Guide that explains both ClientSessions (which are the main building block) and transactions themselves. In short, SpringData provides you with everything you need to leverage Spring managed transaction support in your project. To use it, declare MongoTransactionManager in your configuration, as the following example shows:

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Hands on MongoDB 4.0 transactions with Spring Data

With MongoDB 4.0, ACID transactions have arrived in the Document store, enforcing all-or-nothing execution and maintaining data integrity. So, let’s get straight to it by looking at both the synchronous and the reactive execution models.

At the time of this writing, MongoDB multi-document transactions are supported across a single replica set and feel like the transactions you are probably familiar with from relational databases. Looking at the driver API, one feels immediately at home:

try (ClientSession session = client.startSession()) {

    session.startTransaction();

    try {

        collection.insertOne(session, documentOne);
        collection.insertOne(session, documentTwo);

        session.commitTransaction();

    } catch (Exception e) {
        session.abortTransaction();
    }
}
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Spring Data Lovelace M3 released

On behalf of the Spring Data team, I’m pleased to announce the availability of the third milestone of the Lovelace release train.

This release ships with updates for all store modules that contain new features, improvements, and bug fixes. Notable changes include:

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New in Spring Data Lovelace M2 - Get ready for MongoDB 3.6 and 4.0.

With the latest Spring Data Lovelace Milestone 2 release, the MongoDB module is stacking up new features that are coming your way in the near future. As you might have followed in the news, MongoDB 4 is going to bring ACID transactions to the Document store. The latest MongoDB 3.6 server release already ships with the main building block for those, client sessions.

You can read all about isolation levels and causal consistency in the MongoDB reference. In short, sessions let you execute operations in an order that respects their causal relationships.

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Spring Data Lovelace M1 released.

On behalf of the Spring Data team I’m happy to announce the first milestone of the Lovelace release train. The release ships over 200 tickets fixed! The most important new features are:

  • JPA 2.2 result streaming.
  • MongoDB Validator and JsonSchema support.
  • Support for MongoDB Change Streams.
  • Neo4J OGM 3.1 upgrade.
  • Exist/Count projections as well as a fluent template API in Spring Data for Apache Cassandra.
  • Spring Data for Apache Geode added JCache Annotation support.
  • Query By Example for Redis repository abstractions.
  • Spring Data REST offers more fine grained method exposure mechanisms.
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Spring Data Ingalls SR5 released

On behalf of the Spring Data team, I’d like to announce the availability of Ingalls SR5 release.
It ships with over 40 issues fixed in total and is therefore a recommended upgrade for all users. For your convenience the service release is going to be picked up by the upcoming Spring Boot 1.5.5.

The complete list of issues fixed can be found here.

Spring Data Ingalls SR5

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Spring Data Release Train Kay RC1 & RC2 Released

On behalf of the Spring Data team, I’d like to announce the availability of the first and second release candiate of Spring Data Kay. This release ships over 120 tickets fixed. The curated changelog can be found in our release wiki, the complete list of issues fixed can be found here. Due to a severe issue in RC1 we immediately issued RC2.

Notable changes

  • Enhanced tooling support by adding @NonNullApi and @Nullable annotations in Spring Data Commons to be picked up by your favorite IDE.
  • Fine-tuning of the fluent API for MongoDB including a reactive counterpart and aggregation support.
  • Spring Data for Apache Geode joins the release train.
  • RedisCache got overhauled and is now way easier to configure.
  • Cassandra 3.0 driver upgrade and support for @Indexed and @SASI.
  • Child document support for Spring Data for Apache Solr.
  • A lot of internal cleanups.
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