Based on our record, Apache Flink should be more popular than Hibernate. It has been mentiond 30 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 6 days ago
I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 26 days ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 2 months ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago
Hibernate is the umbrella for a collection of libraries, most notably Hibernate ORM which provides Object/Relational Mapping for java domain objects. In addition to its own "native" API, Hibernate ORM is also an implementation of the Java Persistence API (jpa) specification. - Source: dev.to / over 1 year ago
I'm using Spring Data JPA as a persistence framework. Therefore, those classes are Hibernate entities. - Source: dev.to / over 1 year ago
To prevent SQL Injection attacks to sanitize input data. You can either validate every single input or validate using parameter binding. Parameter binding is mostly used by developers as it offers efficiency and security. If you are using a popular ORM such as sequelize, hibernate, etc then they already provide the functions to validate and sanitize your data. If you are using database modules other than ORM such... - Source: dev.to / almost 2 years ago
JPA is an API for talking to SQL databases and mapping SQL tables to Java classes. You mentioned being familiar with Entity Framework, JPA is somewhat similar. In Java it is more common than in C# to have a specification for something, and then a number of implementations of that specification. JPA is the specification, https://hibernate.org/ is one of the implementations of that spec. If you know you're going to... Source: almost 2 years ago
The answer is that you're using a different version of hibernate than you're looking at the documents for. Your docs link is REALLY old. The oldest version of docs that hibernate.org has on their site where you can easily find them is 4.2 and in that version (maybe even older ones, probably started in 4) .addAnnotatedClassis inConfiguration`. Source: over 2 years ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Sequelize - Provides access to a MySQL database by mapping database entries to objects and vice-versa.
Entity Framework - See Comparison of Entity Framework vs NHibernate.
Spark Mail - Spark helps you take your inbox under control. Instantly see what’s important and quickly clean up the rest. Spark for Teams allows you to create, discuss, and share email with your colleagues