DBMS > EJDB vs. Google Cloud Firestore vs. Hawkular Metrics vs. Hyprcubd vs. Ingres

System Properties Comparison EJDB vs. Google Cloud Firestore vs. Hawkular Metrics vs. Hyprcubd vs. Ingres

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Serverless Time Series DBMS

Well established RDBMS

Primary database model

Document store

Time Series DBMS

Relational DBMS

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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Website

github.com/Softmotions/ejdb

firebase.google.com/products/firestore

www.hawkular.org

hyprcubd.com (offline)

www.actian.com/databases/ingres

Technical documentation

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

firebase.google.com/docs/firestore

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.actian.com/ingres

Developer

Softmotions

Google

Community supported by Red Hat

Hyprcubd, Inc.

Actian Corporation

Initial release

2012

2017

2014

1974

originally developed at University Berkely in early 1970s

Current release

11.2, May 2022

License

Commercial or Open Source

Open Source

GPLv2

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

Java

Server operating systems

server-less

hosted

Linux
OS X
Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

time, int, uint, float, string

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

in-process shared library

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

HTTP REST

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

based on Cassandra

Ingres Replicator

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

MVCC

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.

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.

token access

fine grained access rights according to SQL-standard

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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