DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Bangdb vs. EJDB vs. Google Cloud Firestore

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Bangdb vs. EJDB vs. Google Cloud Firestore

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Editorial information provided by DB-Engines

Name

Description

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

Converged and high performance database for device data, events, time series, document and graph

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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.

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

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	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

bangdb.com

github.com/Softmotions/ejdb

firebase.google.com/products/firestore

Technical documentation

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

docs.bangdb.com

github.com/Softmotions/ejdb/blob/master/README.md

firebase.google.com/docs/firestore

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Sachin Sinha, BangDB

Softmotions

Google

Initial release

2016

2012

2017

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

GPLv2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Server operating systems

hosted

Linux

server-less

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

string, integer, double, bool, date, object_id

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

SQL like support with command line tool

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

in-process shared library

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

Supported programming languages

C
Java
Perl
Python
R

C
C#
C++
Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, Notifications (with Streaming only)

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor, Knob for CAP (enterprise version only)

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

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

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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