DBMS > Google Cloud Datastore vs. mSQL vs. Sequoiadb vs. Tkrzw vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. mSQL vs. Sequoiadb vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

NewSQL database with distributed OLTP and SQL

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Relational DBMS

Document store
Relational DBMS

Key-value store

Relational DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

cloud.google.com/datastore

hughestech.com.au/products/msql

www.sequoiadb.com

dbmx.net/tkrzw

yaacomo.com

Technical documentation

cloud.google.com/datastore/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Google

Hughes Technologies

Sequoiadb Ltd.

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2008

1994

2013

2020

2009

Current release

4.4, October 2021

0.9.3, August 2020

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2.0

commercial

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

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Linux
macOS

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

yes

oid, date, timestamp, binary, regex

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

SQL-like query language (GQL)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

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

JDBC
ODBC

proprietary protocol using JSON

JDBC
ODBC

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C++
Java
PHP
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

JavaScript

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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.

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

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

using specific database classes

yes

User concepts

Access control

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

simple password-based access control

fine grained access rights according to SQL-standard

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