DBMS > Alibaba Cloud Table Store vs. AnzoGraph DB vs. Google Cloud Firestore vs. Netezza vs. Snowflake

System Properties Comparison Alibaba Cloud Table Store vs. AnzoGraph DB vs. Google Cloud Firestore vs. Netezza vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/table-store

cambridgesemantics.com/anzograph

firebase.google.com/products/firestore

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

firebase.google.com/docs/firestore

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Cambridge Semantics

Google

IBM

Snowflake Computing Inc.

Initial release

2016

2018

2017

2000

2014

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

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.

Server operating systems

hosted

Linux

hosted

Linux

included in appliance

hosted

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

schema-free

yes

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

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

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

HTTP API

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Java
Python

C++
Java
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes, Firebase Rules & Cloud Functions

yes

user defined functions

Triggers

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication in MPP-Cluster

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

Atomic single-row operations

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

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 rights based on subaccounts and tokens

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Users with fine-grained authorization concept

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

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