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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Apache Flink vs IBM DB2

Apache Flink vs IBM DB2

OverviewDecisionsComparisonAlternatives

Overview

IBM DB2
IBM DB2
Stacks245
Followers254
Votes19
Apache Flink
Apache Flink
Stacks534
Followers879
Votes38
GitHub Stars25.4K
Forks13.7K

IBM DB2 vs Apache Flink: What are the differences?

Developers describe IBM DB2 as "A family of database server products developed by IBM". DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs. On the other hand, Apache Flink is detailed as "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.

IBM DB2 belongs to "Databases" category of the tech stack, while Apache Flink can be primarily classified under "Big Data Tools".

"Rock solid and very scalable" is the top reason why over 5 developers like IBM DB2, while over 6 developers mention "Unified batch and stream processing" as the leading cause for choosing Apache Flink.

Apache Flink is an open source tool with 9.11K GitHub stars and 4.86K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

According to the StackShare community, Apache Flink has a broader approval, being mentioned in 20 company stacks & 21 developers stacks; compared to IBM DB2, which is listed in 7 company stacks and 9 developer stacks.

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Advice on IBM DB2, 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

IBM DB2
IBM DB2
Apache Flink
Apache Flink

DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.

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
-
GitHub Stars
25.4K
GitHub Forks
-
GitHub Forks
13.7K
Stacks
245
Stacks
534
Followers
254
Followers
879
Votes
19
Votes
38
Pros & Cons
Pros
  • 7
    Rock solid and very scalable
  • 5
    BLU Analytics is amazingly fast
  • 2
    Easy
  • 2
    Secure by default
  • 2
    Native XML support
Pros
  • 16
    Unified batch and stream processing
  • 8
    Easy to use streaming apis
  • 8
    Out-of-the box connector to kinesis,s3,hdfs
  • 4
    Open Source
  • 2
    Low latency
Integrations
Node.js
Node.js
JavaScript
JavaScript
PHP
PHP
Ruby
Ruby
Java
Java
Python
Python
C#
C#
.NET
.NET
C++
C++
Perl
Perl
YARN Hadoop
YARN Hadoop
Hadoop
Hadoop
HBase
HBase
Kafka
Kafka

What are some alternatives to IBM DB2, Apache Flink?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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