Oracle PL/SQL vs Fauna | What are the differences? | StackShare

FaunaDB vs Oracle PL/SQL

Overview

Oracle PL/SQL

Stacks748

Followers598

Votes8

Fauna

Stacks112

Followers153

Votes27

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

Developers describe Oracle PL/SQL as "It is a combination of SQL along with the procedural features of programming languages". 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. On the other hand, FaunaDB is detailed as "The database built for serverless, featuring native GraphQL". FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness and scale. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

Oracle PL/SQL and FaunaDB are primarily classified as "Query Languages" and "Databases" tools respectively.

🔥 Trending in Databases on StackShare

PostgreSQL Databases

A powerful, open source object-relational database system

Try it View Docs Alternatives

Try

431

83.9k

Detailed Comparison

Oracle PL/SQL	Fauna
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.	Escape the boundaries imposed by legacy databases with a data API that is simple to adopt, highly productive to use, and offers the capabilities that your business needs, without the operational pain typically associated with databases.
-	Native support for GraphQL and others. Easily access any data with any API. No middleware necessary.; Access all data via a data model that best suits your needs - relational, document, graph or composite.; A unique approach to indexing makes it simpler to write efficient queries that scale with your application.; Build SaaS apps more easily with native multi-tenancy and query-level QoS controls to prevent workload collisions.; Eliminate data anomalies with multi-region ACID transactions that don't limit number of keys or documents.; Data-driven RBAC that combines with SSL to offers reliable protection, and yet is simple to understand and codify.; Travel back in time with temporal querying. Run queries at a point-in-time or as change feeds. Track how your data evolved.; Dynamically replicates your data to global locations, so that your queries run fast no matter where your users are.; Easily deploy a FaunaDB cluster on your workstation accompanied by a powerful shell and tools to simplify your workflow.;
Statistics
Stacks 748	Stacks 112
Followers 598	Followers 153
Votes 8	Votes 27
Pros & Cons
Pros 2 Multiple ways to accomplish the same end 2 Powerful 1 Massive, continuous investment by Oracle Corp 1 Not mysql 1 Pl/sql Cons 2 High commercial license cost	Pros 5 100% ACID 4 Removes server provisioning or maintenance 4 Generous free tier 3 Also supports SQL, CQL 3 No more n+1 problems (+ GraphQL) Cons 1 Must keep app secrets encrypted 1 Susceptible to DDoS (& others) use timeouts throttling 1 Log stack traces to avoid improper exception handling
Integrations
Python PHP .NET Node.js Oracle Hadoop Java	No integrations available

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

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.