DBMS > Alibaba Cloud AnalyticDB for MySQL vs. EJDB vs. Google Cloud Datastore vs. Realm vs. WakandaDB

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. EJDB vs. Google Cloud Datastore vs. Realm vs. WakandaDB

Editorial information provided by DB-Engines

Name

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Document store

Object oriented DBMS

Secondary database models

Document store

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

github.com/Softmotions/ejdb

cloud.google.com/datastore

realm.io

wakanda.github.io

Technical documentation

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

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/datastore/docs

realm.io/docs

wakanda.github.io/doc

Developer

Alibaba

Softmotions

Google

Realm, acquired by MongoDB in May 2019

Wakanda SAS

Initial release

2012

2008

2014

2012

Current release

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2

commercial

Open Source

AGPLv3, extended commercial license 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

C++, JavaScript

Server operating systems

hosted

server-less

hosted

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

SQL-like query language (GQL)

APIs and other access methods

JDBC
ODBC

in-process shared library

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

RESTful HTTP API

Supported programming languages

C#
Java
PHP
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript

Server-side scripts

Stored procedures

yes

using Google App Engine

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Callbacks using the Google Apps Engine

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication using Paxos

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

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

typically not needed, however similar functionality with collection joins possible

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes

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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