DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Firebase Realtime Database vs. GridGain vs. HEAVY.AI vs. Snowflake

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Firebase Realtime Database vs. GridGain vs. HEAVY.AI vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

GridGain is an in-memory computing platform, built on Apache Ignite

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

firebase.google.com/products/realtime-database

www.gridgain.com

github.com/heavyai/heavydb
www.heavy.ai

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

firebase.google.com/docs/database

www.gridgain.com/docs/index.html

docs.heavy.ai

docs.snowflake.net/manuals/index.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Google

acquired by Google 2014

GridGain Systems, Inc.

HEAVY.AI, Inc.

Snowflake Computing Inc.

Initial release

2016

2012

2007

2016

2014

Current release

GridGain 8.5.1

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition 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.

Implementation language

Java, C++, .Net

C++ and CUDA

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

yes

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

yes

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

Java
JavaScript
Objective-C

C#
C++
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

Callbacks are triggered when data changes

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes (replicated cache)

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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

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