FaunaDB vs Microsoft SQL Server

Overview

Microsoft SQL Server

Stacks21.3K

Followers15.5K

Votes540

Fauna

Stacks112

Followers153

Votes27

FaunaDB vs Microsoft SQL Server: What are the differences?

Introduction:

When comparing FaunaDB and Microsoft SQL Server, there are several key differences that distinguish these two databases. Below, we'll outline six specific differences between the two systems.

Architecture: FaunaDB is a globally distributed, multi-model database that offers multi-region replication by default, providing high availability and low latency for global applications. On the other hand, Microsoft SQL Server follows a more traditional client-server architecture, typically deployed in a single region or data center.
Consistency Model: FaunaDB utilizes the Calvin protocol to achieve strong consistency with ACID transactions, ensuring that data remains consistent across multiple regions. Microsoft SQL Server, on the other hand, relies on eventual consistency in its replication mechanisms, which may result in data divergence under certain conditions.
Programming Model: FaunaDB offers a serverless programming model, enabling developers to write functions directly in the database using powerful query languages like FQL. Microsoft SQL Server, on the other hand, utilizes stored procedures for application logic, which are executed on the server side.
Scalability: FaunaDB is designed for horizontal scalability, allowing developers to seamlessly scale out their databases by adding more nodes to the cluster. In contrast, Microsoft SQL Server traditionally scales vertically by upgrading hardware resources on a single server, leading to potential performance limitations.
Pricing Model: FaunaDB adopts a consumption-based pricing model, where users pay for the resources they actually use, making it cost-effective for startups and small businesses. Microsoft SQL Server typically follows a licensing model based on the number of cores or users, which can be more expensive for organizations with fluctuating workloads.
Ecosystem: FaunaDB integrates seamlessly with modern serverless platforms and frameworks like AWS Lambda and Netlify, providing native support for event-driven architectures. Microsoft SQL Server has a strong ecosystem within the Windows environment, with tools and libraries optimized for .NET applications, but may require additional configuration for cloud-native deployments.

In Summary, FaunaDB and Microsoft SQL Server differ in terms of architecture, consistency model, programming model, scalability, pricing model, and ecosystem support, catering to distinct use cases and preferences in database management.

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Advice on Microsoft SQL Server, Fauna

Erin

IT Specialist

Mar 10, 2020

Needs adviceon

Microsoft SQL Server

MySQL

PostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.

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Detailed Comparison

Microsoft SQL Server	Fauna
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	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 21.3K	Stacks 112
Followers 15.5K	Followers 153
Votes 540	Votes 27
Pros & Cons
Pros 139 Reliable and easy to use 101 High performance 95 Great with .net 65 Works well with .net 56 Easy to maintain Cons 4 Expensive Licensing 2 Microsoft 1 Data pages is only 8k 1 Allwayon can loose data in asycronious mode 1 Replication can loose the data	Pros 5 100% ACID 4 Removes server provisioning or maintenance 4 Generous free tier 3 Also supports SQL, CQL 3 Low latency global CDN's Cons 1 Susceptible to DDoS (& others) use timeouts throttling 1 Log stack traces to avoid improper exception handling 1 Must keep app secrets encrypted

What are some alternatives to Microsoft SQL Server, 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.

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.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

FaunaDB vs Microsoft SQL Server: What are the differences?

Introduction:

When comparing FaunaDB and Microsoft SQL Server, there are several key differences that distinguish these two databases. Below, we'll outline six specific differences between the two systems.

Architecture: FaunaDB is a globally distributed, multi-model database that offers multi-region replication by default, providing high availability and low latency for global applications. On the other hand, Microsoft SQL Server follows a more traditional client-server architecture, typically deployed in a single region or data center.
Consistency Model: FaunaDB utilizes the Calvin protocol to achieve strong consistency with ACID transactions, ensuring that data remains consistent across multiple regions. Microsoft SQL Server, on the other hand, relies on eventual consistency in its replication mechanisms, which may result in data divergence under certain conditions.
Programming Model: FaunaDB offers a serverless programming model, enabling developers to write functions directly in the database using powerful query languages like FQL. Microsoft SQL Server, on the other hand, utilizes stored procedures for application logic, which are executed on the server side.
Scalability: FaunaDB is designed for horizontal scalability, allowing developers to seamlessly scale out their databases by adding more nodes to the cluster. In contrast, Microsoft SQL Server traditionally scales vertically by upgrading hardware resources on a single server, leading to potential performance limitations.
Pricing Model: FaunaDB adopts a consumption-based pricing model, where users pay for the resources they actually use, making it cost-effective for startups and small businesses. Microsoft SQL Server typically follows a licensing model based on the number of cores or users, which can be more expensive for organizations with fluctuating workloads.
Ecosystem: FaunaDB integrates seamlessly with modern serverless platforms and frameworks like AWS Lambda and Netlify, providing native support for event-driven architectures. Microsoft SQL Server has a strong ecosystem within the Windows environment, with tools and libraries optimized for .NET applications, but may require additional configuration for cloud-native deployments.

FaunaDB vs Microsoft SQL Server

Overview