DBMS > Alibaba Cloud AnalyticDB for MySQL vs. GeoSpock vs. LokiJS vs. Microsoft Azure Cosmos DB vs. PouchDB

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. GeoSpock vs. LokiJS vs. Microsoft Azure Cosmos DB vs. PouchDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Spatial and temporal data processing engine for extreme data scale

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Document store

Time Series DBMS

Spatial DBMS

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

Score	0.91
Rank	#201	Overall
	#94	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.alibabacloud.com/product/analyticdb-for-mysql

geospock.com

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

pouchdb.com

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

pouchdb.com/guides

Developer

Alibaba

GeoSpock

Microsoft

Apache Software Foundation

Initial release

2014

2012

Current release

2.0, September 2019

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

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

Java, Javascript

JavaScript

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

temporal, categorical

yes

via views

yes

All properties auto-indexed by default

yes

via views

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC

JavaScript API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C#
Java
PHP
Python

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript

Server-side scripts

Stored procedures

yes

View functions in JavaScript

JavaScript

View functions in JavaScript

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

none

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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