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  5. Malloy vs Oracle PL/SQL

Malloy vs Oracle PL/SQL

OverviewComparisonAlternatives

Overview

Oracle PL/SQL
Oracle PL/SQL
Stacks748
Followers598
Votes8
Malloy
Malloy
Stacks0
Followers7
Votes0

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Detailed Comparison

Oracle PL/SQL
Oracle PL/SQL
Malloy
Malloy

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.

It is an experimental language for describing data relationships and transformations. It is both a semantic modeling language and a querying language that runs queries against a relational database. It is currently available on BigQuery and Postgres.

-
Queries compile to SQL, optimized for your database; Computations are modular, composable, reusable, and extendable in ways that are consistent with modern programming paradigms; Excels at querying and producing nested data sets; The fan and chasm traps are solved, making it possible to aggregate anything in one query and reducing the need for fact tables and overly complex SQL; Defaults are smart, and the language is concise (where SQL is verbose and often redundant)
Statistics
Stacks
748
Stacks
0
Followers
598
Followers
7
Votes
8
Votes
0
Pros & Cons
Pros
  • 2
    Multiple ways to accomplish the same end
  • 2
    Powerful
  • 1
    Pl/sql
  • 1
    Massive, continuous investment by Oracle Corp
  • 1
    Extensible to external langiages
Cons
  • 2
    High commercial license cost
No community feedback yet
Integrations
Python
Python
PHP
PHP
.NET
.NET
Node.js
Node.js
Oracle
Oracle
Hadoop
Hadoop
Java
Java
Google BigQuery
Google BigQuery
PostgreSQL
PostgreSQL

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

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.

GraphQL

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

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.

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