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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. FaunaDB vs VelocityDB

FaunaDB vs VelocityDB

OverviewComparisonAlternatives

Overview

VelocityDB
VelocityDB
Stacks1
Followers19
Votes0
Fauna
Fauna
Stacks112
Followers153
Votes27

VelocityDB vs FaunaDB: What are the differences?

VelocityDB: A NoSQL Object Database, extended as Graph Database is VelocityGraph. It is a C# .NET NoSQL Object Database that can be Embedded/Distributed, extended as Graph Database is VelocityGraph. It supports both embedded and distributed deployments; 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.

VelocityDB and FaunaDB belong to "Databases" category of the tech stack.

Some of the features offered by VelocityDB are:

  • Acid Transactional
  • Android
  • Any CPU (32bit/64bit)

On the other hand, FaunaDB provides the following key features:

  • 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.

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Detailed Comparison

VelocityDB
VelocityDB
Fauna
Fauna

It is a C# .NET NoSQL Object Database that can be Embedded/Distributed, extended as Graph Database is VelocityGraph. It supports both embedded and distributed deployments.

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.

Acid Transactional; Android; Any CPU (32bit/64bit); Array support; Auto Increment on a field; Backup & Restore; Choice of data structure to use; Compression of data; Data Fragmentation
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
1
Stacks
112
Followers
19
Followers
153
Votes
0
Votes
27
Pros & Cons
No community feedback yet
Pros
  • 5
    100% ACID
  • 4
    Generous free tier
  • 4
    Removes server provisioning or maintenance
  • 3
    No more n+1 problems (+ GraphQL)
  • 3
    Low latency global CDN's
Cons
  • 1
    Log stack traces to avoid improper exception handling
  • 1
    Must keep app secrets encrypted
  • 1
    Susceptible to DDoS (& others) use timeouts throttling
Integrations
MySQL
MySQL
PostgreSQL
PostgreSQL
Velocity.js
Velocity.js
.NET
.NET
GraphQL
GraphQL
C#
C#
No integrations available

What are some alternatives to VelocityDB, 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.

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.

Amazon DynamoDB

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

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