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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Azure SQL Database vs FaunaDB

Azure SQL Database vs FaunaDB

OverviewComparisonAlternatives

Overview

Azure SQL Database
Azure SQL Database
Stacks585
Followers502
Votes13
Fauna
Fauna
Stacks112
Followers153
Votes27

Azure SQL Database vs FaunaDB: What are the differences?

Azure SQL Database: Managed, intelligent SQL in the cloud. It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software; FaunaDB: 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.

Azure SQL Database and FaunaDB belong to "Databases" category of the tech stack.

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Detailed Comparison

Azure SQL Database
Azure SQL Database
Fauna
Fauna

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

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
585
Stacks
112
Followers
502
Followers
153
Votes
13
Votes
27
Pros & Cons
Pros
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable
Pros
  • 5
    100% ACID
  • 4
    Generous free tier
  • 4
    Removes server provisioning or maintenance
  • 3
    Works well with GraphQL
  • 3
    No more n+1 problems (+ GraphQL)
Cons
  • 1
    Must keep app secrets encrypted
  • 1
    Log stack traces to avoid improper exception handling
  • 1
    Susceptible to DDoS (& others) use timeouts throttling

What are some alternatives to Azure SQL Database, Fauna?

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.

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

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.

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