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  1. Stackups
  2. Application & Data
  3. Databases
  4. Orm
  5. Apache Flink vs Hibernate

Apache Flink vs Hibernate

OverviewDecisionsComparisonAlternatives

Overview

Hibernate
Hibernate
Stacks1.8K
Followers1.2K
Votes34
GitHub Stars0
Forks0
Apache Flink
Apache Flink
Stacks534
Followers879
Votes38
GitHub Stars25.4K
Forks13.7K

Apache Flink vs Hibernate: What are the differences?

Apache Flink: Fast and reliable large-scale data processing engine. Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala; Hibernate: Idiomatic persistence for Java and relational databases. Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper.

Apache Flink and Hibernate are primarily classified as "Big Data" and "Object Relational Mapper (ORM)" tools respectively.

"Unified batch and stream processing" is the top reason why over 6 developers like Apache Flink, while over 9 developers mention "Easy ORM" as the leading cause for choosing Hibernate.

Apache Flink is an open source tool with 9.36K GitHub stars and 5.01K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

Bodybuilding.com, StyleShare Inc., and Zola are some of the popular companies that use Hibernate, whereas Apache Flink is used by Zalando, sovrn Holdings, and BetterCloud. Hibernate has a broader approval, being mentioned in 87 company stacks & 74 developers stacks; compared to Apache Flink, which is listed in 20 company stacks and 22 developer stacks.

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Advice on Hibernate, Apache Flink

Nilesh
Nilesh

Technical Architect at Self Employed

Jul 8, 2020

Needs adviceonElasticsearchElasticsearchKafkaKafka

We have a Kafka topic having events of type A and type B. We need to perform an inner join on both type of events using some common field (primary-key). The joined events to be inserted in Elasticsearch.

In usual cases, type A and type B events (with same key) observed to be close upto 15 minutes. But in some cases they may be far from each other, lets say 6 hours. Sometimes event of either of the types never come.

In all cases, we should be able to find joined events instantly after they are joined and not-joined events within 15 minutes.

576k views576k
Comments

Detailed Comparison

Hibernate
Hibernate
Apache Flink
Apache Flink

Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper.

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

-
Hybrid batch/streaming runtime that supports batch processing and data streaming programs.;Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.;Flexible and expressive windowing semantics for data stream programs;Built-in program optimizer that chooses the proper runtime operations for each program;Custom type analysis and serialization stack for high performance
Statistics
GitHub Stars
0
GitHub Stars
25.4K
GitHub Forks
0
GitHub Forks
13.7K
Stacks
1.8K
Stacks
534
Followers
1.2K
Followers
879
Votes
34
Votes
38
Pros & Cons
Pros
  • 22
    Easy ORM
  • 8
    Easy transaction definition
  • 3
    Is integrated with spring jpa
  • 1
    Open Source
Cons
  • 3
    Can't control proxy associations when entity graph used
Pros
  • 16
    Unified batch and stream processing
  • 8
    Out-of-the box connector to kinesis,s3,hdfs
  • 8
    Easy to use streaming apis
  • 4
    Open Source
  • 2
    Low latency
Integrations
Java
Java
YARN Hadoop
YARN Hadoop
Hadoop
Hadoop
HBase
HBase
Kafka
Kafka

What are some alternatives to Hibernate, Apache Flink?

Sequelize

Sequelize

Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and more.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Presto

Presto

Distributed SQL Query Engine for Big Data

Prisma

Prisma

Prisma is an open-source database toolkit. It replaces traditional ORMs and makes database access easy with an auto-generated query builder for TypeScript & Node.js.

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Doctrine 2

Doctrine 2

Doctrine 2 sits on top of a powerful database abstraction layer (DBAL). One of its key features is the option to write database queries in a proprietary object oriented SQL dialect called Doctrine Query Language (DQL), inspired by Hibernates HQL.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

MikroORM

MikroORM

TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns. Supports MongoDB, MySQL, MariaDB, PostgreSQL and SQLite databases.

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