DBMS > Alibaba Cloud TSDB vs. Google Cloud Datastore vs. Snowflake vs. Vitess vs. Yanza

System Properties Comparison Alibaba Cloud TSDB vs. Google Cloud Datastore vs. Snowflake vs. Vitess vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

A stable, reliable, and cost-effective online high-performance time series database service

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

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

cloud.google.com/datastore

www.snowflake.com

vitess.io

yanza.com

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

cloud.google.com/datastore/docs

docs.snowflake.net/manuals/index.html

vitess.io/docs

Developer

Alibaba

Google

Snowflake Computing Inc.

The Linux Foundation, PlanetScale

Yanza

Initial release

2008

2014

2013

2015

Current release

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Server operating systems

hosted

Docker
Linux
macOS

Windows

Data scheme

schema-free

yes

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

yes

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

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)

yes

with proprietary extensions

APIs and other access methods

HTTP REST

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

CLI Client
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API

Supported programming languages

Java

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

JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

using Google App Engine

user defined functions

yes

proprietary syntax

Triggers

Callbacks using the Google Apps Engine

similar concept for controling cloud resources

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

Multi-source replication
Source-replica replication

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

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Access managed on TSDB instance level

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

Users with fine-grained authorization concept

no user groups or roles

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