DBMS > FeatureBase vs. Google Cloud Firestore vs. LeanXcale vs. TigerGraph

System Properties Comparison FeatureBase vs. Google Cloud Firestore vs. LeanXcale vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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.

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Graph DBMS

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

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

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

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.featurebase.com

firebase.google.com/products/firestore

www.leanxcale.com

www.tigergraph.com

Technical documentation

docs.featurebase.com

firebase.google.com/docs/firestore

docs.tigergraph.com

Developer

Molecula and Pilosa Open Source Contributors

Google

LeanXcale

Initial release

2017

2015

2017

Current release

2022, May 2022

License

Commercial or Open Source

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++

Server operating systems

Linux
macOS

hosted

Linux

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL queries

yes

through Apache Derby

SQL-like query language (GSQL)

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Java
Python

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

C
Java
Scala

C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source 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

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

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

Role-based access control

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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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