DBMS > Apache Drill vs. EsgynDB vs. Google Cloud Firestore vs. SAP HANA

System Properties Comparison Apache Drill vs. EsgynDB vs. Google Cloud Firestore vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

drill.apache.org

www.esgyn.cn

firebase.google.com/products/firestore

www.sap.com/products/hana.html

Technical documentation

drill.apache.org/docs

firebase.google.com/docs/firestore

help.sap.com/hana

Developer

Apache Software Foundation

Esgyn

Google

SAP

Initial release

2012

2015

2017

2010

Current release

1.20.3, January 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

hosted

Appliance or cloud-service

Data scheme

schema-free

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 SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

JDBC
ODBC

Supported programming languages

C++

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

SQLScript, R

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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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