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  1. Stackups
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  4. Databases
  5. Azure Data Factory vs Vertica

Azure Data Factory vs Vertica

OverviewDecisionsComparisonAlternatives

Overview

Vertica
Vertica
Stacks88
Followers120
Votes16
Azure Data Factory
Azure Data Factory
Stacks253
Followers484
Votes0
GitHub Stars516
Forks610

Vertica vs Azure Data Factory: What are the differences?

What is 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.

What is Azure Data Factory? Create, Schedule, & Manage Data Pipelines. It is a service designed to allow developers to integrate disparate data sources. It is a platform somewhat like SSIS in the cloud to manage the data you have both on-prem and in the cloud.

Vertica and Azure Data Factory can be categorized as "Big Data" tools.

Some of the features offered by Vertica are:

  • 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

On the other hand, Azure Data Factory provides the following key features:

  • Real-Time Integration
  • Parallel Processing
  • Data Chunker

Azure Data Factory is an open source tool with 150 GitHub stars and 255 GitHub forks. Here's a link to Azure Data Factory's open source repository on GitHub.

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Advice on Vertica, Azure Data Factory

Vamshi
Vamshi

Data Engineer at Tata Consultancy Services

May 29, 2020

Needs adviceonPySparkPySparkAzure Data FactoryAzure Data FactoryDatabricksDatabricks

I have to collect different data from multiple sources and store them in a single cloud location. Then perform cleaning and transforming using PySpark, and push the end results to other applications like reporting tools, etc. What would be the best solution? I can only think of Azure Data Factory + Databricks. Are there any alternatives to #AWS services + Databricks?

269k views269k
Comments

Detailed Comparison

Vertica
Vertica
Azure Data Factory
Azure Data Factory

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

It is a service designed to allow developers to integrate disparate data sources. It is a platform somewhat like SSIS in the cloud to manage the data you have both on-prem and in the cloud.

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
Real-Time Integration; Parallel Processing; Data Chunker; Data Masking; Proactive Monitoring; Big Data Processing
Statistics
GitHub Stars
-
GitHub Stars
516
GitHub Forks
-
GitHub Forks
610
Stacks
88
Stacks
253
Followers
120
Followers
484
Votes
16
Votes
0
Pros & Cons
Pros
  • 3
    Shared nothing or shared everything architecture
  • 1
    Partition pruning and predicate push down on Parquet
  • 1
    Vertica is the only product which offers partition prun
  • 1
    Query-Optimized Storage
  • 1
    Fully automated Database Designer tool
No community feedback yet
Integrations
Oracle
Oracle
Golang
Golang
MongoDB
MongoDB
MySQL
MySQL
Sass
Sass
Mode
Mode
PowerBI
PowerBI
Tableau
Tableau
Talend
Talend
Octotree
Octotree
Java
Java
.NET
.NET

What are some alternatives to Vertica, Azure Data Factory?

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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