DBMS > Google Cloud Datastore vs. JSqlDb vs. Lovefield vs. searchxml vs. Yanza

System Properties Comparison Google Cloud Datastore vs. JSqlDb vs. Lovefield vs. searchxml vs. Yanza

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

JavaScript Query Language Database, stores JavaScript objects and primitives

Embeddable relational database for web apps written in pure JavaScript

DBMS for structured and unstructured content wrapped with an application server

Time Series DBMS for IoT Applications

Primary database model

Document store

Document store
Object oriented DBMS

Relational DBMS

Native XML DBMS
Search engine

Time Series DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

cloud.google.com/datastore

jsqldb.org (offline)

google.github.io/lovefield

www.searchxml.net/category/products

yanza.com

Technical documentation

cloud.google.com/datastore/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

www.searchxml.net/support/handouts

Developer

Google

Konrad von Backstrom

Google

informationpartners gmbh

Yanza

Initial release

2008

2018

2014

2015

Current release

0.8, December 2018

2.1.12, February 2017

1.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Server operating systems

hosted

Linux
macOS
Windows

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

tested with Chrome, Firefox, IE, Safari

Windows

Data scheme

schema-free

yes

schema-free

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)

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

RESTful HTTP API
WebDAV
XQuery
XSLT

HTTP API

Supported programming languages

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

JavaScript

C++

most other programming languages supported via APIs

any language that supports HTTP calls

Server-side scripts

Stored procedures

using Google App Engine

functions in JavaScript

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

Using read-only observers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

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 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

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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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