Amazon AppFlow vs Vertica

Overview

Vertica

Stacks88

Followers120

Votes16

Amazon AppFlow

Stacks9

Followers42

Votes0

Vertica vs Amazon AppFlow: What are the differences?

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; Amazon AppFlow: *Securely integrate apps and automate data flows at any scale, without code *. It is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. With AppFlow, you can run data flows at nearly any scale at the frequency you choose - on a schedule, in response to a business event, or on demand. You can configure data transformation capabilities like filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps. AppFlow automatically encrypts data in motion, and allows users to restrict data from flowing over the public Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security threats.

Vertica can be classified as a tool in the "Databases" category, while Amazon AppFlow is grouped under "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, Amazon AppFlow provides the following key features:

Point and click user interface
Native SaaS integrations
Enterprise grade data transformations

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Detailed Comparison

Vertica	Amazon AppFlow
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.	It is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. With AppFlow, you can run data flows at nearly any scale at the frequency you choose - on a schedule, in response to a business event, or on demand. You can configure data transformation capabilities like filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps. AppFlow automatically encrypts data in motion, and allows users to restrict data from flowing over the public Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security threats.
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	Point and click user interface; Native SaaS integrations; Enterprise grade data transformations; High scale data transfer; Data privacy defaults through PrivateLink; Custom encryption keys; IAM policy enforcement; Flexible data flow triggers; Easy to use field mapping; Built in reliability
Statistics
Stacks 88	Stacks 9
Followers 120	Followers 42
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 Golang MongoDB MySQL Sass Mode PowerBI Tableau Talend	Google Analytics Slack Dynatrace Datadog Zendesk Marketo Snowflake Amplitude Veeva

What are some alternatives to Vertica, Amazon AppFlow?

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.