Apache Flink vs Vertica

Overview

Vertica

Stacks88

Followers120

Votes16

Apache Flink

Stacks534

Followers879

Votes38

GitHub Stars25.4K

Forks13.7K

Apache Flink vs Vertica: 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; Vertica: Storage platform designed to handle large volumes of data. It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

Apache Flink and Vertica can be primarily classified as "Big Data" tools.

Some of the features offered by Apache Flink are:

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

On the other hand, Vertica provides the following key features:

Analyze All of Your Data. No longer move data or settle for siloed views
Achieve Scale and Performance
Fear of growing data volumes and users is a thing of the past

Apache Flink is an open source tool with 9.81K GitHub stars and 5.26K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

Zalando, sovrn Holdings, and BetterCloud are some of the popular companies that use Apache Flink, whereas Vertica is used by Taboola, HomeUnion, and Points International. Apache Flink has a broader approval, being mentioned in 29 company stacks & 96 developers stacks; compared to Vertica, which is listed in 3 company stacks and 3 developer stacks.

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CLI (Node.js)

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Advice on Vertica, Apache Flink

Nilesh

Technical Architect at Self Employed

Jul 8, 2020

Needs adviceon

Elasticsearch

Kafka

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.

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Comments

Detailed Comparison

Vertica	Apache Flink
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.	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.
Analyze All of Your Data. No longer move data or settle for siloed views;Achieve Scale and Performance;Fear of growing data volumes and users is a thing of the past;Future-Proof Your Analytics	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 88	Stacks 534
Followers 120	Followers 879
Votes 16	Votes 38
Pros & Cons
Pros 3 Shared nothing or shared everything architecture 1 Vertica is the only product which offers partition prun 1 Query-Optimized Storage 1 Fully automated Database Designer tool 1 Near-Real-Time Analytics in pure Column Store	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
Oracle Golang MongoDB MySQL Sass Mode PowerBI Tableau Talend	YARN Hadoop Hadoop HBase Kafka

What are some alternatives to Vertica, Apache Flink?

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

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

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

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 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

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 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

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.

Related Comparisons

Some of the features offered by Apache Flink are:

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

On the other hand, Vertica provides the following key features:

Analyze All of Your Data. No longer move data or settle for siloed views
Achieve Scale and Performance
Fear of growing data volumes and users is a thing of the past

Apache Flink is an open source tool with 9.81K GitHub stars and 5.26K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

Apache Flink vs Vertica