DBMS > EJDB vs. Google Cloud Firestore vs. HyperSQL vs. RocksDB

System Properties Comparison EJDB vs. Google Cloud Firestore vs. HyperSQL vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Relational DBMS

Key-value store

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

github.com/Softmotions/ejdb

firebase.google.com/products/firestore

hsqldb.org

rocksdb.org

Technical documentation

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

firebase.google.com/docs/firestore

hsqldb.org/web/hsqlDocsFrame.html

github.com/facebook/rocksdb/wiki

Developer

Softmotions

Google

Facebook, Inc.

Initial release

2012

2017

2001

2013

Current release

2.7.2, June 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

based on BSD license

Open Source

BSD

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

Java

C++

Server operating systems

server-less

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

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

HTTP API

JDBC via HTTP
JDBC
ODBC

C++ API
Java API

Supported programming languages

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

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

All languages supporting JDBC/ODBC
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Java, SQL

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

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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