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

Amazon DocumentDB vs VelocityDB

OverviewComparisonAlternatives

Overview

VelocityDB
VelocityDB
Stacks1
Followers19
Votes0
Amazon DocumentDB
Amazon DocumentDB
Stacks72
Followers64
Votes0

VelocityDB vs Amazon DocumentDB: 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; Amazon DocumentDB: Fast, scalable, highly available MongoDB-compatible database service. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

VelocityDB belongs to "Databases" category of the tech stack, while Amazon DocumentDB can be primarily classified under "NoSQL Database as a Service".

Some of the features offered by VelocityDB are:

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

On the other hand, Amazon DocumentDB provides the following key features:

  • MongoDB-compatible
  • Fully managed
  • Performance at scale

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Detailed Comparison

VelocityDB
VelocityDB
Amazon DocumentDB
Amazon DocumentDB

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.

Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

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
MongoDB-compatible;Fully managed;Performance at scale
Statistics
Stacks
1
Stacks
72
Followers
19
Followers
64
Votes
0
Votes
0
Pros & Cons
No community feedback yet
Pros
  • 0
    Easy Setup
  • 0
    Scalable
  • 0
    Storage elasticity
Integrations
MySQL
MySQL
PostgreSQL
PostgreSQL
Velocity.js
Velocity.js
.NET
.NET
GraphQL
GraphQL
C#
C#
No integrations available

What are some alternatives to VelocityDB, Amazon DocumentDB?

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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