DBMS > Galaxybase vs. Google Cloud Firestore vs. Greenplum vs. LeanXcale

System Properties Comparison Galaxybase vs. Google Cloud Firestore vs. Greenplum vs. LeanXcale

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

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.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Graph DBMS

Document store

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

galaxybase.com

firebase.google.com/products/firestore

greenplum.org

www.leanxcale.com

Technical documentation

firebase.google.com/docs/firestore

docs.greenplum.org

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Pivotal Software Inc.

LeanXcale

Initial release

2017

2005

2015

Current release

Nov 20, November 2021

7.0.0, September 2023

License

Commercial or Open Source

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 and Java

Server operating systems

Linux

hosted

Linux

Data scheme

Strong typed schema

schema-free

yes

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

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

JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Go
Java
Python

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

C
Java
Perl
Python
R

C
Java
Scala

Server-side scripts

Stored procedures

user defined procedures and functions

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Role-based access control

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

fine grained access rights according to SQL-standard

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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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