DBMS > Google Cloud Datastore vs. Kingbase vs. Memcached vs. MySQL vs. TypeDB

System Properties Comparison Google Cloud Datastore vs. Kingbase vs. Memcached vs. MySQL vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

In-memory key-value store, originally intended for caching

Widely used open source RDBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Key/Value like access via memcached API

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

cloud.google.com/datastore

Technical documentation

cloud.google.com/datastore/docs

github.com/memcached/memcached/wiki

dev.mysql.com/doc

typedb.com/docs

Developer

Google

BeiJing KINGBASE Information technologies inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

since 2010, originally MySQL AB, then Sun

Vaticle

Initial release

2008

1999

2003

1995

2016

Current release

V8.0, August 2021

1.6.27, May 2024

8.4.0, April 2024

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 3, 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and Java

C and C++

Java

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Proprietary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

using Google App Engine

user defined functions

yes

proprietary syntax

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication
Source-replica replication

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

not for MyISAM storage engine

substituted by the relationship feature

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

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)

fine grained access rights according to SQL-standard

yes

using SASL (Simple Authentication and Security Layer) protocol

Users with fine-grained authorization concept

no user groups or roles

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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