DBMS > Bangdb vs. Google Cloud Firestore vs. Lovefield vs. Microsoft Azure Synapse Analytics

System Properties Comparison Bangdb vs. Google Cloud Firestore vs. Lovefield vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

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

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.

Embeddable relational database for web apps written in pure JavaScript

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

bangdb.com

firebase.google.com/products/firestore

google.github.io/lovefield

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.bangdb.com

firebase.google.com/docs/firestore

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.microsoft.com/azure/synapse-analytics

Developer

Sachin Sinha, BangDB

Google

Microsoft

Initial release

2012

2017

2014

2016

Current release

BangDB 2.0, October 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

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

C, C++

JavaScript

C++

Server operating systems

Linux

hosted

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

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

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

JavaScript

C#
Java
PHP

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Transact SQL

Triggers

yes, Notifications (with Streaming only)

yes, with Cloud Functions

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

yes

using MemoryDB

User concepts

Access control

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.

yes

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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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