DBMS > AlaSQL vs. Google Cloud Bigtable vs. Snowflake vs. Yanza

System Properties Comparison AlaSQL vs. Google Cloud Bigtable vs. Snowflake vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Description

JavaScript DBMS library

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Cloud-based data warehousing service for structured and semi-structured data

Time Series DBMS for IoT Applications

Primary database model

Document store
Relational DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

alasql.org

cloud.google.com/bigtable

www.snowflake.com

yanza.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigtable/docs

docs.snowflake.net/manuals/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Google

Snowflake Computing Inc.

Yanza

Initial release

2014

2015

2014

2015

License

Commercial or Open Source

Open Source

MIT-License

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

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Implementation language

JavaScript

Server operating systems

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

hosted

Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

CLI Client
JDBC
ODBC

HTTP API

Supported programming languages

JavaScript

C#
C++
Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

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

yes

User concepts

Access control

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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