Oracle PL/SQL vs Vertica

Overview

Vertica

Stacks88

Followers120

Votes16

Oracle PL/SQL

Stacks748

Followers598

Votes8

Oracle PL/SQL vs Vertica: What are the differences?

Introduction

In this article, we will explore the key differences between Oracle PL/SQL and Vertica. These two database management systems have their unique features and characteristics, which set them apart from each other. Understanding these differences can help in making an informed decision when choosing the right database management system for a particular use case.

Performance: One of the significant differences between Oracle PL/SQL and Vertica is their performance capabilities. Oracle PL/SQL is known for its robustness and versatility, making it suitable for a wide range of applications. On the other hand, Vertica is specifically designed for handling large volumes of data efficiently, making it ideal for analytical workloads and business intelligence applications.
Scalability: Another key difference is in terms of scalability. Oracle PL/SQL is a traditional relational database management system that supports horizontal scaling by adding more servers. Vertica, on the other hand, is a columnar database management system that utilizes a shared-nothing architecture. This architecture allows for seamless scalability by adding more nodes to the cluster.
Data Compression: Oracle PL/SQL and Vertica also differ in their approach to data compression. Oracle PL/SQL offers various compression techniques like basic table compression, advanced row compression, and hybrid columnar compression. In contrast, Vertica utilizes a unique compression algorithm known as the Vertica Compression Algorithm (VCA), which is specifically designed to optimize columnar storage and improve query performance.
Data Partitioning: Data partitioning is another area where Oracle PL/SQL and Vertica differ. Oracle PL/SQL offers different partitioning strategies like range partitioning, hash partitioning, and list partitioning, allowing for efficient data storage and retrieval. Vertica, on the other hand, utilizes a technique called projections, which automatically divide the data into a series of equally-sized segments based on the values of a particular column. This approach simplifies data management and enhances query performance.
Data Analytics Capabilities: Oracle PL/SQL and Vertica also differ in terms of their data analytics capabilities. Oracle PL/SQL provides a comprehensive set of analytical functions and tools that support complex data analysis and reporting tasks. Vertica, on the other hand, is specifically designed for analytical workloads and offers advanced analytics features like in-database analytics, machine learning, and geospatial analysis.
Data Loading and ETL: The process of loading and transforming data is another area where Oracle PL/SQL and Vertica differ. Oracle PL/SQL provides various tools and utilities like SQL*Loader and Oracle Data Integrator for data loading and ETL (Extract, Transform, Load) processes. Vertica, on the other hand, offers its own ETL tool called Vertica Copy Command, which provides high-speed data loading capabilities and supports parallel data transfer.

In Summary, Oracle PL/SQL and Vertica differ in terms of their performance, scalability, data compression, data partitioning, data analytics capabilities, and data loading/ETL processes. These differences make each database management system suitable for different use cases and specific requirements.

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Detailed Comparison

Vertica	Oracle PL/SQL
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.	It is a powerful, yet straightforward database programming language. It is easy to both write and read, and comes packed with lots of out-of-the-box optimizations and security 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;Future-Proof Your Analytics	-
Statistics
Stacks 88	Stacks 748
Followers 120	Followers 598
Votes 16	Votes 8
Pros & Cons
Pros 3 Shared nothing or shared everything architecture 1 Reduce costs as reduced hardware is required 1 Partition pruning and predicate push down on Parquet 1 Vertica is the only product which offers partition prun 1 Query-Optimized Storage	Pros 2 Multiple ways to accomplish the same end 2 Powerful 1 Not mysql 1 Pl/sql 1 Extensible to external langiages Cons 2 High commercial license cost
Integrations
Oracle Golang MongoDB MySQL Sass Mode PowerBI Tableau Talend	Python PHP .NET Node.js Oracle Hadoop Java

What are some alternatives to Vertica, Oracle PL/SQL?

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.

GraphQL

GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.

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.

Related Comparisons

Oracle PL/SQL vs Vertica: What are the differences?

Introduction

Performance: One of the significant differences between Oracle PL/SQL and Vertica is their performance capabilities. Oracle PL/SQL is known for its robustness and versatility, making it suitable for a wide range of applications. On the other hand, Vertica is specifically designed for handling large volumes of data efficiently, making it ideal for analytical workloads and business intelligence applications.
Scalability: Another key difference is in terms of scalability. Oracle PL/SQL is a traditional relational database management system that supports horizontal scaling by adding more servers. Vertica, on the other hand, is a columnar database management system that utilizes a shared-nothing architecture. This architecture allows for seamless scalability by adding more nodes to the cluster.
Data Compression: Oracle PL/SQL and Vertica also differ in their approach to data compression. Oracle PL/SQL offers various compression techniques like basic table compression, advanced row compression, and hybrid columnar compression. In contrast, Vertica utilizes a unique compression algorithm known as the Vertica Compression Algorithm (VCA), which is specifically designed to optimize columnar storage and improve query performance.
Data Partitioning: Data partitioning is another area where Oracle PL/SQL and Vertica differ. Oracle PL/SQL offers different partitioning strategies like range partitioning, hash partitioning, and list partitioning, allowing for efficient data storage and retrieval. Vertica, on the other hand, utilizes a technique called projections, which automatically divide the data into a series of equally-sized segments based on the values of a particular column. This approach simplifies data management and enhances query performance.
Data Analytics Capabilities: Oracle PL/SQL and Vertica also differ in terms of their data analytics capabilities. Oracle PL/SQL provides a comprehensive set of analytical functions and tools that support complex data analysis and reporting tasks. Vertica, on the other hand, is specifically designed for analytical workloads and offers advanced analytics features like in-database analytics, machine learning, and geospatial analysis.
Data Loading and ETL: The process of loading and transforming data is another area where Oracle PL/SQL and Vertica differ. Oracle PL/SQL provides various tools and utilities like SQL*Loader and Oracle Data Integrator for data loading and ETL (Extract, Transform, Load) processes. Vertica, on the other hand, offers its own ETL tool called Vertica Copy Command, which provides high-speed data loading capabilities and supports parallel data transfer.

Oracle PL/SQL vs Vertica

Overview

Oracle PL/SQL vs Vertica: What are the differences?