DBMS > Google Cloud Bigtable vs. VelocityDB vs. Vitess

System Properties Comparison Google Cloud Bigtable vs. VelocityDB vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store
Wide column store

Graph DBMS
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.66
Rank	#92	Overall
	#15	Key-value stores
	#6	Wide column stores

Score	0.00
Rank	#381	Overall
	#40	Graph DBMS
	#19	Object oriented DBMS

Score	0.99
Rank	#185	Overall
	#84	Relational DBMS

Website

cloud.google.com/bigtable

velocitydb.com

vitess.io

Technical documentation

cloud.google.com/bigtable/docs

velocitydb.com/UserGuide

vitess.io/docs

Developer

Google

VelocityDB Inc

The Linux Foundation, PlanetScale

Initial release

2015

2011

2013

Current release

7.x

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

Any that supports .NET

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.Net

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Based on Windows Authentication

Users with fine-grained authorization concept

no user groups or roles

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