DBMS > Alibaba Cloud MaxCompute vs. FatDB vs. Google Cloud Datastore vs. searchxml vs. Tkrzw

System Properties Comparison Alibaba Cloud MaxCompute vs. FatDB vs. Google Cloud Datastore vs. searchxml vs. Tkrzw

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Document store
Key-value store

Document store

Native XML DBMS
Search engine

Key-value store

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

Score	0.78
Rank	#221	Overall
	#102	Relational DBMS

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.09
Rank	#354	Overall
	#51	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

cloud.google.com/datastore

www.searchxml.net/category/products

dbmx.net/tkrzw

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cloud.google.com/datastore/docs

www.searchxml.net/support/handouts

Developer

Alibaba

FatCloud

Google

informationpartners gmbh

Mikio Hirabayashi

Initial release

2016

2012

2008

2015

2020

Current release

1.0

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Windows

hosted

Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

Via inetgration in SQL Server

SQL-like query language (GQL)

APIs and other access methods

Fluentd
Flume
MaxCompute Console

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Java

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

C++

most other programming languages supported via APIs

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

yes

via applications

using Google App Engine

yes

on the application server

Triggers

yes

via applications

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Multi-source replication using Paxos

yes

sychronisation to multiple collections

none

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

Eventual Consistency
Immediate Consistency

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

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

multiple readers, single writer

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

User concepts

Access control

Access rights for users and roles

Can implement custom security layer via applications

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

Domain, group and role-based access control at the document level and for application services

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